Expectation Modulates the Effect of Deep Brain Stimulation on Motor and Cognitive Function in Tremor-Dominant Parkinson's Disease

Expectation contributes to placebo and nocebo responses in Parkinson''s disease (PD). While there is evidence for expectation-induced modulations of bradykinesia, little is known about the impact of expectation on resting tremor. Subthalamic nucleus (STN) deep brain stimulation (DBS) improves cardinal PD motor symptoms including tremor whereas impairment of verbal fluency (VF) has been observed as a potential side-effect. Here we investigated how expectation modulates the effect of STN-DBS on resting tremor and its interaction with VF. In a within-subject-design, expectation of 24 tremor-dominant PD patients regarding the impact of STN-DBS on motor symptoms was manipulated by verbal suggestions (positive [placebo], negative [nocebo], neutral [control]). Patients participated with (MedON) and without (MedOFF) antiparkinsonian medication. Resting tremor was recorded by accelerometry and bradykinesia of finger tapping and diadochokinesia were assessed by a 3D ultrasound motion detection system. VF was quantified by lexical and semantic tests. In a subgroup of patients, the effect of STN-DBS on tremor was modulated by expectation, i.e. tremor decreased (placebo response) or increased (nocebo response) by at least 10% as compared to the control condition while no significant effect was observed for the overall group. Interestingly, nocebo responders in MedON were additionally characterized by significant impairment in semantic verbal fluency. In contrast, bradykinesia was not affected by expectation. These results indicate that the therapeutic effect of STN-DBS on tremor can be modulated by expectation in a subgroup of patients and suggests that tremor is also among the parkinsonian symptoms responsive to placebo and nocebo interventions. While positive expectations enhanced the effect of STN-DBS by further decreasing the magnitude of tremor, negative expectations counteracted the therapeutic effect and at the same time exacerbated a side-effect often associated with STN-DBS. The present findings underscore the potency of patients'' expectation and its relevance for therapeutic outcomes.     

Association of Systemic Collagen Type IV Formation with Survival among Patients Undergoing Hemodialysis

Objective

The 7S domain of collagen type IV (P4NP_7S) assessed in plasma represents systemic collagen type IV formation. The objective of the study was to investigate the association of systemic collagen type IV formation with survival among patients undergoing hemodialysis.

Methods

We performed an observational cohort study of 371 hemodialysis patients. Plasma P4NP_7S was analyzed using a specific enzyme-linked immunosorbent assay detecting the amino-terminal propeptide of type IV procollagen. Association between categories of plasma P4NP_7S concentrations and survival was initially assessed by Kaplan-Meier analysis, then in an adjusted Cox model.

Results

For hemodialysis patients in the highest category of systemic collagen type IV formation, i.e. plasma P4NP_7S concentrations more than 775 pg/L, an increased risk for death was observed (highest P4NP_7S category vs all other categories, hazard ratio, 1.934; 95% confidence interval, 1.139 to 3.285). Survival analysis showed an increased risk of death in the highest P4NP_7S category compared to the other categories (Chi square 6.903; P = 0.032). Median survival was only 105 days in the highest P4NP_7S category whereas it was 629 days in the medium category, and 905 days in the lowest category. Multivariable-adjusted Cox regression showed increased odds for death with higher age and higher P4NP_7S categories. Systemic collagen type IV formation was associated with plasma concentrations of the collagen IV degradation product C4M (Spearman r = 0.764; P<0.0001) confirming extracellular matrix turnover.

Conclusion

Among hemodialysis patients elevated systemic collagen type IV formation suggesting accelerating systemic fibrosis was associated with increased risk of death.     

Localization of Microfibrillar-Associated Protein 4 (MFAP4) in Human Tissues: Clinical Evaluation of Serum MFAP4 and Its Association with Various Cardiovascular Conditions

Microfibrillar-associated protein 4 (MFAP4) is located in the extracellular matrix (ECM). We sought to identify tissues with high levels of MFAP4 mRNA and MFAP4 protein expression. Moreover, we aimed to evaluate the significance of MFAP4 as a marker of cardiovascular disease (CVD) and to correlate MFAP4 with other known ECM markers, such as fibulin-1, osteoprotegerin (OPG), and osteopontin (OPN). Quantitative real-time PCR demonstrated that MFAP4 mRNA was more highly expressed in the heart, lung, and intestine than in other elastic tissues. Immunohistochemical studies demonstrated high levels of MFAP4 protein mainly at sites rich in elastic fibers and within blood vessels in all tissues investigated. The AlphaLISA technique was used to determine serum MFAP4 levels in a clinical cohort of 172 patients consisting of 5 matched groups with varying degrees of CVD: 1: patients with ST elevation myocardial infarction (STEMI), 2: patients with non-STEMI, 3: patients destined for vascular surgery because of various atherosclerotic diseases (stable atherosclerotic disease), 4: apparently healthy individuals with documented coronary artery calcification (CAC-positive), and 5: apparently healthy individuals without signs of coronary artery calcification (CAC-negative). Serum MFAP4 levels were significantly lower in patients with stable atherosclerotic disease than CAC-negative individuals (p<0.05). Furthermore, lower serum MFAP4 levels were present in patients with stable atherosclerotic disease compared with STEMI and non-STEMI patients (p<0.05). In patients with stable atherosclerotic disease, positive correlations between MFAP4 and both fibulin-1 (ρ = 0.50; p = 0.0244) and OPG (ρ = 0.62; p = 0.0014) were found. Together, these results indicate that MFAP4 is mainly located in elastic fibers and is highly expressed in blood vessels. The present study suggests that serum MFAP4 varies in groups of patients with different cardiovascular conditions. Further studies are warranted to describe the role of serum MFAP4 as a biomarker of stable atherosclerotic disease.     

Biomass Yield and Greenhouse Gas Emissions from a Drained Fen Peatland Cultivated with Reed Canary Grass under Different Harvest and Fertilizer Regimes

Reed canary grass (RCG, Phalaris arundinacea L.) is a suitable energy crop for cultivation in northern peatlands. However, the atmospheric impact of RCG cultivation as influenced by harvest frequency and fertilization is not clear. Here, we compared the biomass yield and greenhouse gas (GHG) balance for RCG cultivation in peatlands affected by cutting frequency and fertilizer managements. The managements included one-cut (OC) and two-cut (TC) systems that were either fertilized (TC-F) or unfertilized (TC-U) after the first cut in summer. Biomass yield of OC, TC-F and TC-U were 12, 16 and 11 Mg dry biomass per hectare per year, respectively. GHG fluxes of CO₂, N₂O and CH₄ were measured with closed chamber techniques in the period between first and second (final) harvest of the TC managements, i.e. from 15 June to 23 September 2011. In the GHG monitoring period of 100 days, all systems were net sources of CO₂ corresponding to 64?±?3, 217?±?15 and 50?±?23 g?CO₂-C?m^?2 (mean?±?standard error, n?=?3) from the OC, TC-F and TC-U systems, respectively. In the same period, emissions of N₂O from TC-F were ten times higher as compared to OC and TC-U. Emissions of CH₄ were negligible from all systems. The TC systems could not improve the GHG balance during cultivation (271, 663 and 210 g CO₂e-C?m^?2 emissions from the OC, TC-F and TC-U systems, respectively), but in a broader GHG life cycle perspective, the increased biomass yield by TC-F could replace more fossil fuel and offset at least some of the higher emissions from the system.     

Complete genome sequence of Desulfocapsa sulfexigens,a marine deltaproteobacterium specialized in disproportionating inorganic sulfur compounds

Desulfocapsa sulfexigens SB164P1 (DSM 10523) belongs to the deltaproteobacterial family Desulfobulbaceae and is one of two validly described members of its genus. This strain was selected for genome sequencing, because it is the first marine bacterium reported to thrive on the disproportionation of elemental sulfur, a process with a unresolved enzymatic pathway in which elemental sulfur serves both as electron donor and electron acceptor. Furthermore, in contrast to its phylogenetically closest relatives, which are dissimilatory sulfate-reducers, D. sulfexigens is unable to grow by sulfate reduction and appears metabolically specialized in growing by disproportionating elemental sulfur, sulfite or thiosulfate with CO₂ as the sole carbon source. The genome of D. sulfexigens contains the set of genes that is required for nitrogen fixation. In an acetylene assay it could be shown that the strain reduces acetylene to ethylene, which is indicative for N-fixation. The circular chromosome of D. sulfexigens SB164P1 comprises 3,986,761 bp and harbors 3,551 protein-coding genes of which 78% have a predicted function based on auto-annotation. The chromosome furthermore encodes 46 tRNA genes and 3 rRNA operons.     

A Simple Iterative Model Accurately Captures Complex Trapline Formation by Bumblebees Across Spatial Scales and Flower Arrangements

Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees'' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments.     

Serum Iron Levels and the Risk of Parkinson Disease: A Mendelian Randomization Study

Background

Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date.

Methods and Findings

We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%–6%; p = 0.001) per 10 µg/dl increase in serum iron.

Conclusions

Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made. Please see later in the article for the Editors'' Summary     

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex.