Numerical modelling of plasticity induced by transcranial magnetic stimulation

We use neural field theory and spike-timing dependent plasticity to make a simple but biophysically reasonable model of long-term plasticity changes in the cortex due to transcranial magnetic stimulation (TMS). We show how common TMS protocols can be captured and studied within existing neural field theory. Specifically, we look at repetitive TMS protocols such as theta burst stimulation and paired-pulse protocols. Continuous repetitive protocols result mostly in depression, but intermittent repetitive protocols in potentiation. A paired pulse protocol results in depression at short (∼ 100 ms) interstimulus intervals, but potentiation for mid-range intervals. The model is sensitive to the choice of neural populations that are driven by the TMS pulses, and to the parameters that describe plasticity, which may aid interpretation of the high variability in existing experimental results. Driving excitatory populations results in greater plasticity changes than driving inhibitory populations. Modelling also shows the merit in optimizing a TMS protocol based on an individual’s electroencephalogram. Moreover, the model can be used to make predictions about protocols that may lead to improvements in repetitive TMS outcomes

Characteristics of temporal fluctuations in the hyperpolarized state of the cortical slow oscillation

We present evidence for the hypothesis that transitions between the low- and high-firing states of the cortical slow oscillation correspond to neuronal phase transitions. By analyzing intracellular recordings of the membrane potential during the cortical slow oscillation in rats, we quantify the temporal fluctuations in power and the frequency centroid of the power spectrum in the period of time before “down” to “up” transitions. By taking appropriate averages over such events, we present these statistics as a function of time before transition. The results demonstrate an increase in fluctuation power and time scale broadly consistent with the slowing of systems close to phase transitions. The analysis is complicated and limited by the difficulty in identifying when transitions begin, and removing dc trends in membrane potential

Striatal mRNA expression patterns underlying peak dose L-DOPA-induced dyskinesia in the 6-OHDA hemiparkinsonian rat

L-DOPA is the primary pharmacological treatment for relief of the motor symptoms of Parkinson’s disease (PD). With prolonged treatment (⩾5 years) the majority of patients will develop abnormal involuntary movements as a result of L-DOPA treatment, known as L-DOPA-induced dyskinesia. Understanding the underlying mechanisms of dyskinesia is a crucial step toward developing treatments for this debilitating side effect. We used the 6-hydroxydopamine (6-OHDA) rat model of PD treated with a three-week dosing regimen of L-DOPA plus the dopa decarboxylase inhibitor benserazide (4 mg/kg and 7.5 mg/kg s.c., respectively) to induce dyskinesia in 50% of individuals. We then used RNA-seq to investigate the differences in mRNA expression in the striatum of dyskinetic animals, non-dyskinetic animals, and untreated parkinsonian controls at the peak of dyskinesia expression, 60 min after L-DOPA administration. Overall, 255 genes were differentially expressed; with significant differences in mRNA expression observed between all three groups. In dyskinetic animals 129 genes were more highly expressed and 14 less highly expressed when compared with non-dyskinetic and untreated parkinsonian controls. In L-DOPA treated animals 42 genes were more highly expressed and 95 less highly expressed when compared with untreated parkinsonian controls. Gene set cluster analysis revealed an increase in expression of genes associated with the cytoskeleton and phosphoproteins in dyskinetic animals compared with non-dyskinetic animals, which is consistent with recent studies documenting an increase in synapses in dyskinetic animals. These genes may be potential targets for drugs to ameliorate L-DOPA-induced dyskinesia or as an adjunct treatment to prevent their occurrence

A system for accurate and automated injection of hyperpolarized substrate with minimal dead time and scalable volumes over a large range

Over recent years hyperpolarization by dissolution dynamic nuclear polarization has become an established technique for studying metabolism in vivo in animal models. Temporal signal plots obtained from the injected metabolite and daughter products, e.g. pyruvate and lactate, can be fitted to compartmental models to estimate kinetic rate constants. Modeling and physiological parameter estimation can be made more robust by consistent and reproducible injections through automation. An injection system previously developed by us was limited in the injectable volume to between 0.6 and 2.4 ml and injection was delayed due to a required syringe filling step. An improved MR-compatible injector system has been developed that measures the pH of injected substrate, uses flow control to reduce dead volume within the injection cannula and can be operated over a larger volume range. The delay time to injection has been minimized by removing the syringe filling step by use of a peristaltic pump. For 100 ll to 10.000 ml, the volume range typically used for mice to rabbits, the average delivered volume was 97.8% of the demand volume. The standard deviation of delivered volumes was 7 ll for 100 ll and 20 ll for 10.000 ml demand volumes (mean S.D. was 9 ul in this range). In three repeat injections through a fixed 0.96 mm O.D. tube the coefficient of variation for the area under the curve was 2%. For in vivo injections of hyperpolarized pyruvate in tumor-bearing rats, signal was first detected in the input femoral vein cannula at 3–4 s post-injection trigger signal and at 9–12 s in tumor tissue. The pH of the injected pyruvate was 7.1 ± 0.3 (mean ± S.D., n = 10). For small injection volumes, e.g. less than 100 ll, the internal diameter of the tubing contained within the peristaltic pump could be reduced to improve accuracy. Larger injection volumes are limited only by the size of the receiving vessel connected to the pump

Means-end analysis of consumers’ perceptions of virtual world affordances for e-commerce

Virtual worlds are three-dimensional (3D) persistent multi-user online environments where users interact through avatars. The affordances of virtual worlds can be useful for business-to-consumer e-commerce. Moreover, affordances of virtual worlds can complement affordances of websites to provide consumers with an enhanced e-commerce experience. We investigated which affordances of virtual worlds can enhance consumers‟ experiences on e-commerce websites. We conducted laddering interviews with 30 virtual world consumers to understand their perceptions of virtual world affordances. A means-end analysis was then applied to the interview data. The results suggest co-presence, product discovery, 3D product experience, greater interactivity with products and sociability are some of the key virtual world affordances for consumers. We discuss theoretical implications of the research using dimensions from the Technology Acceptance Model. We also discuss practical implications, such as how virtual world affordances can be incorporated into the design of e-commerce websites

Fast variability from black-hole binaries

Currently available information on fast variability of the X-ray emission from accreting collapsed objects constitutes a complex phenomenology which is difficult to interpret. We review the current observational standpoint for black-hole binaries and survey models that have been proposed to interpret it. Despite the complex structure of the accretion flow, key observational diagnostics have been identified which can provide direct access to the dynamics of matter motions in the close vicinity of black holes and thus to the some of fundamental properties of curved spacetimes, where strong-field general relativistic effects can be observed.Comment: 20 pages, 11 figures. Accepted for publication in Space Science Reviews. Also to appear in hard cover in the Space Sciences Series of ISSI "The Physics of Accretion onto Black Holes" (Springer Publisher

Identifying demographic, social and clinical predictors of biologic therapy effectiveness in psoriasis: a multicentre longitudinal cohort study.

BACKGROUND: Biologic therapies have revolutionized the treatment of moderate-to-severe psoriasis. However, for reasons largely unknown, many patients do not respond or lose response to these drugs. OBJECTIVES: To evaluate demographic, social and clinical factors that could be used to predict effectiveness and stratify response to biologic therapies in psoriasis. METHODS: Using a multicentre, observational, prospective pharmacovigilance study (BADBIR), we identified biologic-naive patients starting biologics with outcome data at 6 (n = 3079) and 12 (n = 3110) months. Associations between 31 putative predictors and outcomes were investigated in univariate and multivariable regression analyses. Potential stratifiers of treatment response were investigated with statistical interactions. RESULTS: Eight factors associated with reduced odds of achieving = 90% improvement in Psoriasis Area and Severity Index (PASI 90) at 6 months were identified (described as odds ratio and 95% confidence interval): demographic (female sex, 0·78, 0·66-0·93); social (unemployment, 0·67, 0·45-0·99); unemployment due to ill health (0·62, 0·48-0·82); ex- and current smoking (0·81, 0·66-0·99 and 0·79, 0·63-0·99, respectively); clinical factors (high weight, 0·99, 0·99-0·99); psoriasis of the palms and/or soles (0·75, 0·61-0·91); and presence of small plaques only compared with small and large plaques (0·78, 0·62-0·96). White ethnicity (1·48, 1·12-1·97) and higher baseline PASI (1·04, 1·03-1·04) were associated with increased odds of achieving PASI 90. The findings were largely consistent at 12 months. There was little evidence for predictors of differential treatment response. CONCLUSIONS: Psoriasis phenotype and potentially modifiable factors are associated with poor outcomes with biologics, underscoring the need for lifestyle management. Effect sizes suggest that these factors alone cannot inform treatment selection

Increased dietary protein in the second trimester of gestation increases live weight gain and carcass composition in weaner calves to 6 months of age

Genetically similar nulliparous Polled Hereford heifers from a closed pedigree herd were used to evaluate the effects of dietary protein during the first and second trimester of gestation upon fetal, placental and postnatal growth. Heifers were randomly allocated into two groups at 35d post AI (35dpc) to a single bull and fed High (15.7%CP) or Low (5.9%CP) protein in the first trimester (T1). At 90dpc, half of each nutritional treatment group changed to a High or Low protein diet for the second trimester until 180dpc (T2). High protein intake in the second trimester increased birthweight in females (P = 0.05) but there was no effect of treatment upon birthweight when taken over both sexes. Biparietal diameter was significantly increased by high protein in the second trimester with the effect being greater in the female (P = 0.02) but also significant overall (P = 0.05). Placental weight was positively correlated with birth weight, fibroblast volume, and relative blood vessel volume (P < 0.05). Placental fibroblast density was increased and trophoblast volume decreased in the high protein first trimester treatment group (P <0.05). There was a trend for placental weight to be increased by high protein in the second trimester (P = 0.06). Calves from heifers fed the high protein treatment in the second trimester weighed significantly more on all occasions preweaning (at one month (P = 0.0004), 2 mths (P = 0.006), 3 mths (P = 0.002), 4 mths (P = 0.01), 5 mths (P = 41 0.03), 6 mths (P = 0.001)), and grew at a faster rate over the 6 month period. By 6 mths of age the calves from heifers fed high nutrition in the second trimester weighed 33kg heavier than those fed the low diet in the second trimester. These results suggest that dietary protein in early pregnancy alters the development of the bovine placenta and calf growth to weaning

Development of a discrete element model with moving realistic geometry to simulate particle motion in a Mi-Pro granulator

This paper presents the implementation of a methodology incorporating a 3D CAD geometry into a 3D Discrete Element Method (DEM) code; discussing some of the issues which were experienced. The 3D CAD model was discretised into a finite element mesh and the finite wall method was employed for contact detection between the elements and the spherical particles. The geometry was based on a lab scale Mi-Pro granulator. Simulations were performed to represent dry particle motion in this piece of equipment. The model was validated by high speed photography of the particle motion at the surface of the Mi-Pro�s clear bowl walls. The results indicated that the particle motion was dominated by the high speed impeller and that a roping regime exists. The results from this work give a greater insight into the particle motion and can be used to understand the complex interactions which occur within this equipment