Metabolic profiling predicts response to anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis

<p>Objective: Anti–tumor necrosis factor (anti-TNF) therapies are highly effective in rheumatoid arthritis (RA) and psoriatic arthritis (PsA), but a significant number of patients exhibit only a partial or no therapeutic response. Inflammation alters local and systemic metabolism, and TNF plays a role in this. We undertook this study to determine if the patient's metabolic fingerprint prior to therapy could predict responses to anti-TNF agents.</p> <p>Methods: Urine was collected from 16 RA patients and 20 PsA patients before and during therapy with infliximab or etanercept. Urine metabolic profiles were assessed using nuclear magnetic resonance spectroscopy. Discriminating metabolites were identified, and the relationship between metabolic profiles and clinical outcomes was assessed.</p> <p>Results: Baseline urine metabolic profiles discriminated between RA patients who did or did not have a good response to anti-TNF therapy according to European League Against Rheumatism criteria, with a sensitivity of 88.9% and a specificity of 85.7%, with several metabolites contributing (in particular histamine, glutamine, xanthurenic acid, and ethanolamine). There was a correlation between baseline metabolic profiles and the magnitude of change in the Disease Activity Score in 28 joints from baseline to 12 months in RA patients (P = 0.04). In both RA and PsA, urinary metabolic profiles changed between baseline and 12 weeks of anti-TNF therapy. Within the responders, urinary metabolite changes distinguished between etanercept and infliximab treatment.</p> <p>Conclusion: The clear relationship between urine metabolic profiles of RA patients at baseline and their response to anti-TNF therapy may allow development of novel approaches to the optimization of therapy. Differences in metabolic profiles during treatment with infliximab and etanercept in RA and PsA may reflect distinct mechanisms of action.</p&gt

Spin glass overlap barriers in three and four dimensions

For the Edwards-Anderson Ising spin-glass model in three and four dimensions (3d and 4d) we have performed high statistics Monte Carlo calculations of those free-energy barriers $F^q_B$ which are visible in the probability density $P_J(q)$ of the Parisi overlap parameter $q$. The calculations rely on the recently introduced multi-overlap algorithm. In both dimensions, within the limits of lattice sizes investigated, these barriers are found to be non-self-averaging and the same is true for the autocorrelation times of our algorithm. Further, we present evidence that barriers hidden in $q$ dominate the canonical autocorrelation times.Comment: 20 pages, Latex, 12 Postscript figures, revised version to appear in Phys. Rev.

About the Functional Form of the Parisi Overlap Distribution for the Three-Dimensional Edwards-Anderson Ising Spin Glass

Recently, it has been conjectured that the statistics of extremes is of relevance for a large class of correlated system. For certain probability densities this predicts the characteristic large $x$ fall-off behavior $f(x)\sim\exp (-a e^x)$, $a>0$. Using a multicanonical Monte Carlo technique, we have calculated the Parisi overlap distribution $P(q)$ for the three-dimensional Edward-Anderson Ising spin glass at and below the critical temperature, even where $P(q)$ is exponentially small. We find that a probability distribution related to extreme order statistics gives an excellent description of $P(q)$ over about 80 orders of magnitude.Comment: 4 pages RevTex, 3 figure

Ground-state clusters of two-, three- and four-dimensional +-J Ising spin glasses

A huge number of independent true ground-state configurations is calculated for two-, three- and four-dimensional +- J spin-glass models. Using the genetic cluster-exact approximation method, system sizes up to N=20^2,8^3,6^4 spins are treated. A ``ballistic-search'' algorithm is applied which allows even for large system sizes to identify clusters of ground states which are connected by chains of zero-energy flips of spins. The number of clusters n_C diverges with N going to infinity. For all dimensions considered here, an exponential increase of n_C appears to be more likely than a growth with a power of N. The number of different ground states is found to grow clearly exponentially with N. A zero-temperature entropy per spin of s_0=0.078(5)k_B (2d), s_0=0.051(3)k_B (3d) respectively s_0=0.027(5)k_B (4d) is obtained.Comment: large extensions, now 12 pages, 9 figures, 27 reference

Determining the density of states for classical statistical models: A random walk algorithm to produce a flat histogram

We describe an efficient Monte Carlo algorithm using a random walk in energy space to obtain a very accurate estimate of the density of states for classical statistical models. The density of states is modified at each step when the energy level is visited to produce a flat histogram. By carefully controlling the modification factor, we allow the density of states to converge to the true value very quickly, even for large systems. This algorithm is especially useful for complex systems with a rough landscape since all possible energy levels are visited with the same probability. In this paper, we apply our algorithm to both 1st and 2nd order phase transitions to demonstrate its efficiency and accuracy. We obtained direct simulational estimates for the density of states for two-dimensional ten-state Potts models on lattices up to $200 \times 200$ and Ising models on lattices up to $256 \times 256$. Applying this approach to a 3D $\pm J$ spin glass model we estimate the internal energy and entropy at zero temperature; and, using a two-dimensional random walk in energy and order-parameter space, we obtain the (rough) canonical distribution and energy landscape in order-parameter space. Preliminary data suggest that the glass transition temperature is about 1.2 and that better estimates can be obtained with more extensive application of the method.Comment: 22 pages (figures included

Response to Comment on “Mycorrhizal association as a primary control of the CO 2 fertilization effect”

Norby et al. center their critique on the design of the data set and the response variable used. We address these criticisms and reinforce the conclusion that plants that associate with ectomycorrhizal fungi exhibit larger biomass and growth responses to elevated CO2 compared with plants that associate with arbuscular mycorrhizae

Cosmological Parameters Degeneracies and Non-Gaussian Halo Bias

We study the impact of the cosmological parameters uncertainties on the measurements of primordial non-Gaussianity through the large-scale non-Gaussian halo bias effect. While this is not expected to be an issue for the standard LCDM model, it may not be the case for more general models that modify the large-scale shape of the power spectrum. We consider the so-called local non-Gaussianity model and forecasts from planned surveys, alone and combined with a Planck CMB prior. In particular, we consider EUCLID- and LSST-like surveys and forecast the correlations among $f_{\rm NL}$ and the running of the spectral index $\alpha_s$, the dark energy equation of state $w$, the effective sound speed of dark energy perturbations $c^2_s$, the total mass of massive neutrinos $M_\nu=\sum m_\nu$, and the number of extra relativistic degrees of freedom $N_\nu^{rel}$. Neglecting CMB information on $f_{\rm NL}$ and scales $k > 0.03 h$/Mpc, we find that, if $N_\nu^{\rm rel}$ is assumed to be known, the uncertainty on cosmological parameters increases the error on $f_{\rm NL}$ by 10 to 30% depending on the survey. Thus the $f_{\rm NL}$ constraint is remarkable robust to cosmological model uncertainties. On the other hand, if $N_\nu^{\rm rel}$ is simultaneously constrained from the data, the $f_{\rm NL}$ error increases by $\sim 80$. Finally, future surveys which provide a large sample of galaxies or galaxy clusters over a volume comparable to the Hubble volume can measure primordial non-Gaussianity of the local form with a marginalized 1--$\sigma$ error of the order $\Delta f_{\rm NL} \sim 2-5$, after combination with CMB priors for the remaining cosmological parameters. These results are competitive with CMB bispectrum constraints achievable with an ideal CMB experiment.Comment: 17 pages, 1 figure added, typos corrected, comments added, matches the published versio

The Virtual International Stroke Trials Archive

BACKGROUND AND PURPOSE: Stroke has global importance and it causes an increasing amount of human suffering and economic burden, but its management is far from optimal. The unsuccessful outcome of several research programs highlights the need for reliable data on which to plan future clinical trials. The Virtual International Stroke Trials Archive aims to aid the planning of clinical trials by collating and providing access to a rich resource of patient data to perform exploratory analyses. METHODS: Data were contributed by the principal investigators of numerous trials from the past 16 years. These data have been centrally collated and are available for anonymized analysis and hypothesis testing. RESULTS: Currently, the Virtual International Stroke Trials Archive contains 21 trials. There are data on \u3e15,000 patients with both ischemic and hemorrhagic stroke. Ages range between 18 and 103 years, with a mean age of 69+/-12 years. Outcome measures include the Barthel Index, Scandinavian Stroke Scale, National Institutes of Health Stroke Scale, Orgogozo Scale, and modified Rankin Scale. Medical history and onset-to-treatment time are readily available, and computed tomography lesion data are available for selected trials. CONCLUSIONS: This resource has the potential to influence clinical trial design and implementation through data analyses that inform planning

Reexamination of the long-range Potts model: a multicanonical approach

We investigate the critical behavior of the one-dimensional q-state Potts model with long-range (LR) interaction $1/r^{d+\sigma}$, using a multicanonical algorithm. The recursion scheme initially proposed by Berg is improved so as to make it suitable for a large class of LR models with unequally spaced energy levels. The choice of an efficient predictor and a reliable convergence criterion is discussed. We obtain transition temperatures in the first-order regime which are in far better agreement with mean-field predictions than in previous Monte Carlo studies. By relying on the location of spinodal points and resorting to scaling arguments, we determine the threshold value $\sigma_c(q)$ separating the first- and second-order regimes to two-digit precision within the range $3 \leq q \leq 9$. We offer convincing numerical evidence supporting $\sigma_c(q)Comment: 18 pages, 18 figure

On the existence of a Bose Metal at T=0

This paper aims to justify, at a microscopic level, the existence of a two-dimensional Bose metal, i.e. a metallic phase made out of Cooper pairs at T=0. To this end, we consider the physics of quantum phase fluctuations in (granular) superconductors in the absence of disorder and emphasise the role of two order parameters in the problem, viz. phase order and charge order. We focus on the 2-d Bose Hubbard model in the limit of very large fillings, i.e. a 2-d array of Josephson junctions. We find that the algebra of phase fluctuations is that of the Euclidean group $E_{2}$ in this limit, and show that the model is equivalent to two coupled XY models in (2+1)-d, one corresponding to the phase degrees of freedom, and the other the charge degrees of freedom. The Bose metal, then, is the phase in which both these degrees of freedom are disordered(as a result of quantum frustration). We analyse the model in terms of its topological excitations and suggest that there is a strong indication that this state represents a surface of critical points, akin to the gapless spin liquid states. We find a remarkable consistency of this scenario with certain low-T_c thin film experiments.Comment: 16 pages, 2 figure