Quasi-Monopolar Stimulation: A Novel Electrode Design Configuration for Performance Optimization of a Retinal Neuroprosthesis

In retinal neuroprostheses, spatial interaction between electric fields from various electrodes – electric crosstalk – may occur in multielectrode arrays during simultaneous stimulation of the retina. Depending on the electrode design and placement, this crosstalk can either enhance or degrade the functional characteristics of a visual prosthesis. To optimize the device performance, a balance must be satisfied between the constructive interference of crosstalk on dynamic range and power consumption and its negative effect on artificial visual acuity. In the present computational modeling study, we have examined the trade-off in these positive and negative effects using a range of currently available electrode array configurations, compared to a recently proposed stimulation strategy – the quasi monopolar (QMP) configuration – in which the return current is shared between local bipolar guards and a distant monopolar electrode. We evaluate the performance of the QMP configuration with respect to the implantation site and electrode geometry parameters. Our simulation results demonstrate that the beneficial effects of QMP are only significant at electrode-to-cell distances greater than the electrode dimensions. Possessing a relatively lower activation threshold, QMP was found to be superior to the bipolar configuration in terms of providing a relatively higher visual acuity. However, the threshold for QMP was more sensitive to the topological location of the electrode in the array, which may need to be considered when programming the manner in which electrode are simultaneously activated. This drawback can be offset with a wider dynamic range and lower power consumption of QMP. Furthermore, the ratio of monopolar return current to total return can be used to adjust the functional performance of QMP for a given implantation site and electrode parameters. We conclude that the QMP configuration can be used to improve visual information-to-stimulation mapping in a visual prosthesis, while maintaining low power consumption.     

Re-establishment of Calluna vulgaris (L.) Hull in an eight-year grazing experiment on upland acid grassland

Upland heathland is an internationally important habitat but a large area in the UK has been degraded to acid grassland by intensive livestock grazing. Re-establishment of dwarf shrubs, particularly Calluna vulgaris (L.) Hull, is a key objective for restoring heathland on these sites. A replicated plot-scale experiment was set up to examine effects of disturbance and seed addition on C. vulgaris establishment in a Nardus stricta L. grassland under three grazing regimes: sheep only (1.5 ewes ha^?1 for 10 months per year); cattle only (0.5 heifers ha^?1 in summer only); and, the cattle regime combined with sheep (1.0 ewes ha^?1 for 10 months per year). Early results of the experiment have been reported previously but it was not known if these results were an indication of the longer-term restoration success. Here we evaluate the success of the restoration methods (disturbance, seeding treatments and grazing regime) eight years after the treatments began. In seeded plots, young C. vulgaris plants had greatest above-ground height, dry weight and shoot length if grazing was excluded or the cattle-only regime was applied. C. vulgaris cover was greatest, and increased most, in plots that had been disturbed, seeded and ungrazed or subjected to the cattle-only regime. The vegetation in these plots also became more similar to reference sites with 50% or more cover of C. vulgaris. The invasive Juncus effusus L. was more frequent in disturbed and grazed plots but less frequent in plots with C. vulgaris established from added seed. Previous results that showed the benefits of disturbance and seeding treatments were still valid but changes in the vegetation composition were still occurring and longer-term studies will be needed to determine when grazing regimes including sheep might be reintroduced.     

The Ability of Flux Balance Analysis to Predict Evolution of Central Metabolism Scales with the Initial Distance to the Optimum

The most powerful genome-scale framework to model metabolism, flux balance analysis (FBA), is an evolutionary optimality model. It hypothesizes selection upon a proposed optimality criterion in order to predict the set of internal fluxes that would maximize fitness. Here we present a direct test of the optimality assumption underlying FBA by comparing the central metabolic fluxes predicted by multiple criteria to changes measurable by a ¹³C-labeling method for experimentally-evolved strains. We considered datasets for three Escherichia coli evolution experiments that varied in their length, consistency of environment, and initial optimality. For ten populations that were evolved for 50,000 generations in glucose minimal medium, we observed modest changes in relative fluxes that led to small, but significant decreases in optimality and increased the distance to the predicted optimal flux distribution. In contrast, seven populations evolved on the poor substrate lactate for 900 generations collectively became more optimal and had flux distributions that moved toward predictions. For three pairs of central metabolic knockouts evolved on glucose for 600–800 generations, there was a balance between cases where optimality and flux patterns moved toward or away from FBA predictions. Despite this variation in predictability of changes in central metabolism, two generalities emerged. First, improved growth largely derived from evolved increases in the rate of substrate use. Second, FBA predictions bore out well for the two experiments initiated with ancestors with relatively sub-optimal yield, whereas those begun already quite optimal tended to move somewhat away from predictions. These findings suggest that the tradeoff between rate and yield is surprisingly modest. The observed positive correlation between rate and yield when adaptation initiated further from the optimum resulted in the ability of FBA to use stoichiometric constraints to predict the evolution of metabolism despite selection for rate.     

Enduring Effects of Early Life Stress on Firing Patterns of Hippocampal and Thalamocortical Neurons in Rats: Implications for Limbic Epilepsy

Early life stress results in an enduring vulnerability to kindling-induced epileptogenesis in rats, but the underlying mechanisms are not well understood. Recent studies indicate the involvement of thalamocortical neuronal circuits in the progression of kindling epileptogenesis. Therefore, we sought to determine in vivo the effects of early life stress and amygdala kindling on the firing pattern of hippocampus as well as thalamic and cortical neurons. Eight week old male Wistar rats, previously exposed to maternal separation (MS) early life stress or early handling (EH), underwent amygdala kindling (or sham kindling). Once fully kindled, in vivo juxtacellular recordings in hippocampal, thalamic and cortical regions were performed under neuroleptic analgesia. In the thalamic reticular nucleus cells both kindling and MS independently lowered firing frequency and enhanced burst firing. Further, burst firing in the thalamic reticular nucleus was significantly increased in kindled MS rats compared to kindled EH rats (p<0.05). In addition, MS enhanced burst firing of hippocampal pyramidal neurons. Following a stimulation-induced seizure, somatosensory cortical neurons exhibited a more pronounced increase in burst firing in MS rats than in EH rats. These data demonstrate changes in firing patterns in thalamocortical and hippocampal regions resulting from both MS and amygdala kindling, which may reflect cellular changes underlying the enhanced vulnerability to kindling in rats that have been exposed to early life stress.     

Importance of Weight Loss Maintenance and Risk Prediction in the Prevention of Type 2 Diabetes: Analysis of European Diabetes Prevention Study RCT

Background

Prevalence of type 2 diabetes (T2D) is increasing worldwide. T2D prevention by lifestyle intervention is effective. Pragmatic scalable interventions are needed, with evidence to efficiently target and monitor such interventions. We report pooled analyses of data from three European trial cohorts: to analyse T2D incidence, sustained weight loss and utility of risk predictors.

Methods

We analysed data on 749 adults with impaired glucose tolerance (278 men and 471 women, mean age 56 years, mean BMI 31 kgm⁻²) recruited between 1993 and 2003, and randomised to intensive lifestyle intervention (I) or lifestyle advice control (C). The intervention aimed to increase physical activity, modify diet, and promote weight loss≥5%. Using Cox-regression survival analysis, we assessed T2D incidence and the impact on T2D incidence of sustained weight loss, and of baseline cut-point values of FINDRISC score, fasting plasma glucose (FPG), and HbA_1c.

Results

Mean follow-up duration was 3.1 years. T2D was diagnosed in 139 participants (I = 45/379, C = 94/370). Cumulative T2D incidence was 57% lower in the intervention compared with the control group (HR 0.42 (95% CI 0.29 to 0.60) P<0.001). Participants with ≥5% weight loss at one year had 65% lower T2D incidence (HR 0.35 (95% CI 0.22 to 0.56) P<0.001); maintaining ≥5% weight loss for two and three years further reduced T2D incidence. Recommended cut-points to identify those at high risk for T2D would have identified different proportions of European Diabetes Prevention Study (EDIPS) participants with similar hazard-ratios for intervention effect.

Conclusions

Pooled analysis of EDIPS trial data reinforces evidence for T2D prevention by lifestyle intervention. Analysis showed the preventive effect of ≥5% weight loss, especially if maintained long term, which has utility for intervention monitoring. Analysis of proposed cut-points demonstrates difficulties in balancing risk and benefit, to efficiently target interventions and suggests evidence is needed to define clinical policy.

Trial registrations

The Finnish Diabetes Prevention study, Helsinki, Finland: ClinicalTrials.gov; {"type":"clinical-trial","attrs":{"text":"NCT00518167","term_id":"NCT00518167"}}NCT00518167 The SLIM diabetes prevention study, Maastricht, The Netherlands: Clinical Trials.gov; {"type":"clinical-trial","attrs":{"text":"NCT00381186","term_id":"NCT00381186"}}NCT00381186 The EDIPS-Newcastle diabetes prevention study, Newcastle upon Tyne, UK: International Standard Randomised Controlled Trial Number; ISRCTN15670600.     

Variable δ15N Diet-Tissue Discrimination Factors among Sharks: Implications for Trophic Position,Diet and Food Web Models

The application of stable isotopes to characterize the complexities of a species foraging behavior and trophic relationships is dependent on assumptions of δ¹⁵N diet-tissue discrimination factors (∆¹⁵N). As ∆¹⁵N values have been experimentally shown to vary amongst consumers, tissues and diet composition, resolving appropriate species-specific ∆¹⁵N values can be complex. Given the logistical and ethical challenges of controlled feeding experiments for determining ∆¹⁵N values for large and/or endangered species, our objective was to conduct an assessment of a range of reported ∆¹⁵N values that can hypothetically serve as surrogates for describing the predator-prey relationships of four shark species that feed on prey from different trophic levels (i.e., different mean δ¹⁵N dietary values). Overall, the most suitable species-specific ∆¹⁵N values decreased with increasing dietary-δ¹⁵N values based on stable isotope Bayesian ellipse overlap estimates of shark and the principal prey functional groups contributing to the diet determined from stomach content analyses. Thus, a single ∆¹⁵N value was not supported for this speciose group of marine predatory fishes. For example, the ∆¹⁵N value of 3.7‰ provided the highest percent overlap between prey and predator isotope ellipses for the bonnethead shark (mean diet δ¹⁵N = 9‰) whereas a ∆¹⁵N value < 2.3‰ provided the highest percent overlap between prey and predator isotope ellipses for the white shark (mean diet δ¹⁵N = 15‰). These data corroborate the previously reported inverse ∆¹⁵N-dietary δ¹⁵N relationship when both isotope ellipses of principal prey functional groups and the broader identified diet of each species were considered supporting the adoption of different ∆¹⁵N values that reflect the predators’ δ¹⁵N-dietary value. These findings are critical for refining the application of stable isotope modeling approaches as inferences regarding a species’ ecological role in their community will be influenced with consequences for conservation and management actions.     

Adaptive seamless clinical trials using early outcomes for treatment or subgroup selection: Methods,simulation model and their implementation in R

Adaptive seamless designs combine confirmatory testing, a domain of phase III trials, with features such as treatment or subgroup selection, typically associated with phase II trials. They promise to increase the efficiency of development programmes of new drugs, for example, in terms of sample size and/or development time. It is well acknowledged that adaptive designs are more involved from a logistical perspective and require more upfront planning, often in the form of extensive simulation studies, than conventional approaches. Here, we present a framework for adaptive treatment and subgroup selection using the same notation, which links the somewhat disparate literature on treatment selection on one side and on subgroup selection on the other. Furthermore, we introduce a flexible and efficient simulation model that serves both designs. As primary endpoints often take a long time to observe, interim analyses are frequently informed by early outcomes. Therefore, all methods presented accommodate interim analyses informed by either the primary outcome or an early outcome. The R package asd , previously developed to simulate designs with treatment selection, was extended to include subgroup selection (so-called adaptive enrichment designs). Here, we describe the functionality of the R package asd and use it to present some worked-up examples motivated by clinical trials in chronic obstructive pulmonary disease and oncology. The examples both illustrate various features of the R package and provide insights into the operating characteristics of adaptive seamless studies.