Functional lesional neurosurgery for tremor: back to the future?

For nearly a century, functional neurosurgery has been applied in the treatment of tremor. While deep brain stimulation has been in the focus of academic interest in recent years, the establishment of incisionless technology, such as MRI-guided high-intensity focused ultrasound, has again stirred interest in lesional approaches.In this article, we will discuss the historical development of surgical technique and targets, as well as the technological state-of-the-art of conventional and incisionless interventions for tremor due to Parkinson's disease, essential and dystonic tremor and tremor related to multiple sclerosis (MS) and midbrain lesions. We will also summarise technique-inherent advantages of each technology and compare their lesion characteristics. From this, we identify gaps in the current literature and derive future directions for functional lesional neurosurgery, in particularly potential trial designs, alternative targets and the unsolved problem of bilateral lesional treatment. The results of a systematic review and meta-analysis of the consistency, efficacy and side effect rate of lesional treatments for tremor are presented separately alongside this article

Collective Animal Behavior from Bayesian Estimation and Probability Matching

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is based on empirical fits to observations and we lack first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching.
In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability given by the Bayesian estimation that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior

Physics of Neutron Star Crusts

The physics of neutron star crusts is vast, involving many different research fields, from nuclear and condensed matter physics to general relativity. This review summarizes the progress, which has been achieved over the last few years, in modeling neutron star crusts, both at the microscopic and macroscopic levels. The confrontation of these theoretical models with observations is also briefly discussed.Comment: 182 pages, published version available at <http://www.livingreviews.org/lrr-2008-10

‘Fish out of water’: a cross-sectional study on the interaction between social and neighbourhood effects on weight management behaviours

Objective: To analyse whether an individual’s neighbourhood influences the uptake of weight management strategies and whether there is an interaction between individual socio-economic status and neighbourhood deprivation. Methodology: Data were collected from the Yorkshire Health Study (2010–2012) for 27 806 individuals on the use of the following weight management strategies: ‘slimming clubs’, ‘healthy eating’, ‘increasing exercise’ and ‘controlling portion size’. A multi-level logistic regression was fit to analyse the use of these strategies, controlling for age, sex, body mass index, education, neighbourhood deprivation and neighbourhood population turnover (a proxy for neighbourhood social capital). A cross-level interaction term was included for education and neighbourhood deprivation. Lower Super Output Area was used as the geographical scale for the areal unit of analysis. Results: Significant neighbourhood effects were observed for use of ‘slimming clubs’, ‘healthy eating’ and ‘increasing exercise’ as weight management strategies, independent of individual- and area-level covariates. A significant interaction between education and neighbourhood deprivation was observed across all strategies, suggesting that as an area becomes more deprived, individuals of the lowest education are more likely not to use any strategy compared with those of the highest education. Conclusions: Neighbourhoods modify/amplify individual disadvantage and social inequalities, with individuals of low education disproportionally affected by deprivation. It is important to include neighbourhood-based explanations in the development of community-based policy interventions to help tackle obesit

Dual alpha2C/5HT1A receptor agonist allyphenyline induces gastroprotection and inhibits fundic and colonic contractility

Allyphenyline, a novel α2-adrenoceptor (AR) ligand, has been shown to selectively activate α2C-adrenoceptors (AR) and 5HT1A receptors, but also to behave as a neutral antagonist of α2A-ARs. We exploited this unique pharmacological profile to analyze the role of α2C-ARs and 5HT1A receptors in the regulation of gastric mucosal integrity and gastrointestinal motility

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Bayesian Multimodel Inference for Geostatistical Regression Models

The problem of simultaneous covariate selection and parameter inference for spatial regression models is considered. Previous research has shown that failure to take spatial correlation into account can influence the outcome of standard model selection methods. A Markov chain Monte Carlo (MCMC) method is investigated for the calculation of parameter estimates and posterior model probabilities for spatial regression models. The method can accommodate normal and non-normal response data and a large number of covariates. Thus the method is very flexible and can be used to fit spatial linear models, spatial linear mixed models, and spatial generalized linear mixed models (GLMMs). The Bayesian MCMC method also allows a priori unequal weighting of covariates, which is not possible with many model selection methods such as Akaike's information criterion (AIC). The proposed method is demonstrated on two data sets. The first is the whiptail lizard data set which has been previously analyzed by other researchers investigating model selection methods. Our results confirmed the previous analysis suggesting that sandy soil and ant abundance were strongly associated with lizard abundance. The second data set concerned pollution tolerant fish abundance in relation to several environmental factors. Results indicate that abundance is positively related to Strahler stream order and a habitat quality index. Abundance is negatively related to percent watershed disturbance

Measuring the Meltdown: Drivers of Global Amphibian Extinction and Decline

Habitat loss, climate change, over-exploitation, disease and other factors have been hypothesised in the global decline of amphibian biodiversity. However, the relative importance of and synergies among different drivers are still poorly understood. We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk. Multi-model Bayesian inference reveals that large amphibian species with small geographic range and pronounced seasonality in temperature and precipitation are most likely to be Red-Listed by IUCN. Elevated habitat loss and human densities are also correlated with high threat risk. Range size, habitat loss and more extreme seasonality in precipitation contributed to decline risk in the 2,454 species that declined between 1980 and 2004, compared to species that were stable (n = 1,545) or had increased (n = 28). These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation