Tracking daily fatigue fluctuations in multiple sclerosis : ecological momentary assessment provides unique insights

The preparation of this manuscript was supported by a UK Economic and Social Research Council (ESRC) PhD studentship (ES/1026266/1) awarded to DP. The study was funded by the Psychology Unit at the University of Southampton. The authors declare that they have no conflict of interest. The authors thank all participants of this study. Open access via Springer Compact Agreement.Peer reviewedPublisher PD

Computer simulation of protein systems

Ligand binding to dihydrofolate reductase (DHFR) is discussed. This is an extremely important enzyme, as it is the target of several drugs (inhibitors) which are used clinically as antibacterials, antiprotozoals and in cancer chemotherapy. DHFR catalyzes the NADPH (reduced nicotinamide adenine dinucleotide phosphate) dependent reduction of dihydrofolate to tetrahydrofolate, which is used in several pathways of purine and pyrimidine iosynthesis, including that of thymidylate. Since DNA synthesis is dependent on a continuing supply of thymidylate, a blockade of DHFR resulting in a depletion of thymidylate can lead to the cessation of growth of a rapidly proliferating cell line. DHFR exhibits a significant species to species variability in its sensitivity to various inhibitors. For example, trimethoprim, an inhibitor of DHFR, binds to bacterial DHFR's 5 orders of magnitude greater than to vertebrate DHFR's. The structural mechanics, dynamics and energetics of a family of dihydrofolate reductases are studied to rationalize the basis for the inhibitor of these enyzmes and to understand the molecular basis of the difference in the binding constants between the species. This involves investigating the conformational changes induced in the protein on binding the ligand, the internal strain imposed by the enzyme on the ligand, the restriction of fluctuations in atom positions due to binding and the consequent change in entropy

Cluster Algorithm for a Solid-On-Solid Model with Constraints

We adapt the VMR (valleys-to-mountains reflections) algorithm, originally devised by us for simulations of SOS models, to the BCSOS model. It is the first time that a cluster algorithm is used for a model with constraints. The performance of this new algorithm is studied in detail in both phases of the model, including a finite size scaling analysis of the autocorrelations.Comment: 10 pages, 3 figures appended as ps-file

Critical exponents of a three dimensional O(4) spin model

By Monte Carlo simulation we study the critical exponents governing the transition of the three-dimensional classical O(4) Heisenberg model, which is considered to be in the same universality class as the finite-temperature QCD with massless two flavors. We use the single cluster algorithm and the histogram reweighting technique to obtain observables at the critical temperature. After estimating an accurate value of the inverse critical temperature \Kc=0.9360(1), we make non-perturbative estimates for various critical exponents by finite-size scaling analysis. They are in excellent agreement with those obtained with the $4-\epsilon$ expansion method with errors reduced to about halves of them.Comment: 25 pages with 8 PS figures, LaTeX, UTHEP-28

Blockspin Cluster Algorithms for Quantum Spin Systems

Cluster algorithms are developed for simulating quantum spin systems like the one- and two-dimensional Heisenberg ferro- and anti-ferromagnets. The corresponding two- and three-dimensional classical spin models with four-spin couplings are maped to blockspin models with two-blockspin interactions. Clusters of blockspins are updated collectively. The efficiency of the method is investigated in detail for one-dimensional spin chains. Then in most cases the new algorithms solve the problems of slowing down from which standard algorithms are suffering.Comment: 11 page

Recurrent difficulties: solving quantitative problems

Investigating the process students use to solve quantitative problems using a think aloud strategy

Three-dimensional Ising model in the fixed-magnetization ensemble: a Monte Carlo study

We study the three-dimensional Ising model at the critical point in the fixed-magnetization ensemble, by means of the recently developed geometric cluster Monte Carlo algorithm. We define a magnetic-field-like quantity in terms of microscopic spin-up and spin-down probabilities in a given configuration of neighbors. In the thermodynamic limit, the relation between this field and the magnetization reduces to the canonical relation M(h). However, for finite systems, the relation is different. We establish a close connection between this relation and the probability distribution of the magnetization of a finite-size system in the canonical ensemble.Comment: 8 pages, 2 Postscript figures, uses RevTe

On the statistical evaluation of dose-response functions

The linear-quadratic dependence of effect on the dose of ionizing radiation and its biophysical implications are considered. The estimation of the parameters of the response function and the derivation of the joint confidence region of the estimates are described. The method is applied to the induction of pink mutations inTradescantia which follows the linear-quadratic model. The statistical procedure is also suitable for other response functions