Perceived malleability of self versus the world and its impact on youths’ control orientation and well-being in the US, Germany, and India

Primary control is defined as changing the world to fit the self, while secondary control is defined as changing the self to fit the world. To understand why different individuals prefer different kinds of control processes, we proposed a research project looking at US, German and Indian young adults. We hypothesize that theories of self and the world (fixed vs. malleable; Dweck, 1999) affect the prevailing mode of control used. Furthermore, adolescents’ cultural background is assumed to affect their self-world theories as well as the adaptiveness of specific modes of control. For example, in the US, where the self is tended to be seen as fixed and the world as malleable, primary control prevails and is more adaptive than secondary control while the reverse is expected for India. We present the theoretical outline and methodology of the study as well as first results.

Locomotor velocity and striatal adaptive gene expression changes of the direct and indirect pathways in Parkinsonian rats

BACKGROUND In Parkinson's disease (PD), bradykinesia, or slowness of movement, only appears after a large striatal dopamine depletion. Compensatory mechanisms probably play a role in this delayed appearance of symptoms. OBJECTIVE Our hypothesis is that the striatal direct and indirect pathways participate in these compensatory mechanisms. METHODS We used the unilateral 6-hydroxydopamine (6-OHDA) rat model of PD and control animals. Four weeks after the lesion, the spontaneous locomotor activity of the rats was measured and then the animals were killed and their brain extracted. We quantified the mRNA expression of markers of the striatal direct and indirect pathways as well as the nigral expression of dopamine transporter (DAT) and tyrosine hydroxylase (TH) mRNA. We also carried out an immunohistochemistry for the striatal TH protein expression. RESULTS As expected, the unilateral 6-OHDA rats presented a tendency to an ipsilateral head turning and a low locomotor velocity. In 6-OHDA rats only, we observed a significant and positive correlation between locomotor velocity and both D1-class dopamine receptor (D1R) (direct pathway) and enkephalin (ENK) (indirect pathway) mRNA in the lesioned striatum, as well as between D1R and ENK mRNA. CONCLUSIONS Our results demonstrate a strong relationship between both direct and indirect pathways and spontaneous locomotor activity in the parkinsonian rat model. We suggest a synergy between both pathways which could play a role in compensatory mechanisms and may contribute to the delayed appearance of bradykinesia in PD.

Robust estimates of climate-induced hydrological change in a temperate mountainous region

A sustainable water resources management depends on sound information about the impacts of climate change. This information is, however, not easily derived because natural runoff variability interferes with the climate change signal. This study presents a procedure that leads to robust estimates of magnitude and Time Of Emergence (TOE) of climate-induced hydrological change that also account for the natural variability contained in the time series. Firstly, natural variability of 189 mesoscale catchments in Switzerland is sampled for 10 ENSEMBLES scenarios for the control (1984–2005) and two scenario periods (near future: 2025–2046, far future: 2074–2095) applying a bootstrap procedure. Then, the sampling distributions of mean monthly runoff are tested for significant differences with the Wilcoxon-Mann–Whitney test and for effect size with Cliff’s delta d. Finally, the TOE of a climate change induced hydrological change is determined when at least eight out of the ten hydrological projections significantly differ from natural variability. The results show that the TOE occurs in the near future period except for high-elevated catchments in late summer. The significant hydrological projections in the near future correspond, however, to only minor runoff changes. In the far future, hydrological change is statistically significant and runoff changes are substantial. Temperature change is the most important factor determining hydrological change in this mountainous region. Therefore, hydrological change depends strongly on a catchment’s mean elevation. Considering that the hydrological changes are predicted to be robust in the near future highlights the importance of accounting for these changes in water resources planning.

Adaptive Algorithms for Personalized Diabetes Treatment

Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

Early metacognitive abilities: The interplay of monitoring and control processes in 5- to 7-year-old children

The goal of the current investigation was to compare two monitoring processes (judgments of learning [JOLs] and confidence judgments [CJs]) and their corresponding control processes (allocation of study time and selection of answers to maximize accuracy, respectively) in 5- to 7-year-old children (N=101). Children learned the meaning of Japanese characters and provided JOLs after a study phase and CJs after a memory test. They were given the opportunity to control their learning in self-paced study phases, and to control their accuracy by placing correct answers into a treasure chest and incorrect answers into a trash can. All three age groups gave significantly higher CJs for correct compared to incorrect answers, with no age-related differences in the magnitude of this difference, suggesting robust metacognitive monitoring skills in children as young as 5. Furthermore, a link between JOLs and study time was found in the 6- and 7-year-olds, such that children spent more time studying items with low JOLs compared to items with high JOLs. Also, 6- and 7-year-olds but not 5-year-olds spent more time studying difficult items compared to easier items. Moreover, age-related improvements were found in children's use of CJs to guide their selection of answers: although children as young as 5 placed their most confident answers in the treasure chest and least confident answers in the trash can, this pattern was more robust in older children. Overall, results support the view that some metacognitive judgments may be acted upon with greater ease than others among young children.

Self-control in social decision making: A neurobiological perspective

Self-control is defined as the process in which thoughts, emotions, or prepotent responses are inhibited to efficiently enact a more focal goal. Self-control not only allows for more adaptive individual decision making but also promotes adaptive social decision making. In this chapter, we examine a burgeoning area of interdisciplinary research: the neuroscience of self-control in social decision making. We examine research on self-control in complex social contexts examined from a social neuroscience perspective. We review correlational evidence from neuroimaging studies and causal evidence from neuromodulation studies (i.e., brain stimulation). We specifically highlight research that shows that self-control involves the lateral prefrontal cortex (PFC) across a number of social domains and behaviors. Research has also begun to directly integrate nonsocial with social forms of self-control, showing that the basic neurobiological processes involved in stopping a motor response appear to be involved in social contexts that require self-control. Further, neural traits, such as baseline activation in the lateral PFC, can explain sources of individual differences in self-control capacity. We explore whether techniques that change brain functioning could target neural mechanisms related to self-control capacity to potentially enhance self-control in social behavior. Finally, we discuss several research questions ripe for examination. We broadly suggest that future research can now turn to exploring how neural traits and situational affordances interact to impact self-control in social decision making in order to continue to elucidate the processes that allow people to maintain and realize stable goals in a dynamic and often uncertain social environment.

Adaptive servo-ventilation as treatment of persistent central sleep apnea in post-acute ischemic stroke patients.

BACKGROUND Adaptive servo-ventilation (ASV) is a well-established treatment of central sleep apnea (CSA) related to congestive heart failure (CHF). Few studies have evaluated the effectiveness and adherence in patients with CSA of other etiologies, and even less is known about treatment of CSA in patients of post ischemic stroke. METHODS A single-centre retrospective analysis of ASV treatment for CSA in post-acute ischemic stroke patients without concomitant CHF was performed. Demographics, clinical data, sleep studies, ventilator settings, and adherence data were evaluated. RESULTS Out of 154 patients on ASV, 15 patients had CSA related to ischemic stroke and were started on ASV a median of 11 months after the acute cerebrovascular event. Thirteen out of the 15 patients were initially treated with continuous positive airway pressure (11/15) and bilevel positive airway pressure (2/15) therapy with unsatisfactory control of CSA. ASV significantly improved AHI (46.7 ± 24.3 vs 8.5 ± 12/h, P = 0.001) and reduced ESS (8.7 ± 5.7 vs 5.6 ± 2.5, P = 0.08) with a mean nightly use of ASV of 5.4 ± 2.4 h at 3 months after the initiation of treatment. Results were maintained at 6 months. CONCLUSION ASV was well tolerated and clinically effective in this group of patients with persistent CSA after ischemic stroke.

Messung dispositioneller Selbstkontroll-Kapazität: Eine deutsche Adaptation der Kurzform der Self-Control Scale (SCS-K-D)

Self-control is defined as the overriding or modification of one’s own response tendencies. Dispositional self control capacity is positively linked to various kinds of adaptive behavior. In order to economically measure self-control capacity in German-speaking samples, the brief version of the Self-Control Scale by Tangney, Baumeister and Boone (2004) was adapted into German. The translated entire Self-Control Scale consisting of 36 items was administered to university students (N = 316, study 1) and secondary school students (N = 335, study 2). The brief version consisting of 13 items, which were included in the entire scale, proved to be one-dimensional, reliable, and valid in terms of expected correlations with criteria. The comparison between the brief and the entire scale showed that the costs of the more economical brief measure with regard to reliability and validity are low.

Passionate thinkers feel better: Self-control capacity as mediator of the relationship between need for cognition and affective adjustment

The present study tested a possible explanation for the positive relationship between the motivation to engage in cognitive endeavors (need for cognition, NFC) and indicators of affective adjustment (e.g., higher self-esteem, lower depression) that has been demonstrated in previous studies. We suggest that dispositional self-control capacity mediates this relationship, since NFC has been found to be related to self-control capacity, and self-control capacity is crucial for adjustment. NFC, dispositional self-control capacity, self-esteem, habitual depressive mood, and tendency to respond in a socially desirable manner were measured among 150 university students via self-report. Regression analyses and Sobel tests revealed that self-control capacity was a potential mediator of the positive relationship between NFC and affective adjustment. The findings were robust in terms of social desirability.

Indigenous enteric eosinophils control DCs to initiate a primary Th2 immune response in vivo.

Eosinophils natively inhabit the small intestine, but a functional role for them there has remained elusive. Here, we show that eosinophil-deficient mice were protected from induction of Th2-mediated peanut food allergy and anaphylaxis, and Th2 priming was restored by reconstitution with il4(+/+) or il4(-/-) eosinophils. Eosinophils controlled CD103(+) dendritic cell (DC) activation and migration from the intestine to draining lymph nodes, events necessary for Th2 priming. Eosinophil activation in vitro and in vivo led to degranulation of eosinophil peroxidase, a granule protein whose enzymatic activity promoted DC activation in mice and humans in vitro, and intestinal and extraintestinal mouse DC activation and mobilization to lymph nodes in vivo. Further, eosinophil peroxidase enhanced responses to ovalbumin seen after immunization. Thus, eosinophils can be critical contributors to the intestinal immune system, and granule-mediated shaping of DC responses can promote both intestinal and extraintestinal adaptive immunity.

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

Fully Adaptive Newton--Galerkin Methods for Semilinear Elliptic Partial Differential Equations

In this paper we develop an adaptive procedure for the numerical solution of general, semilinear elliptic problems with possible singular perturbations. Our approach combines both prediction-type adaptive Newton methods and a linear adaptive finite element discretization (based on a robust a posteriori error analysis), thereby leading to a fully adaptive Newton–Galerkin scheme. Numerical experiments underline the robustness and reliability of the proposed approach for various examples

Addition of docetaxel, zoledronic acid, or both to first-line long-term hormone therapy in prostate cancer (STAMPEDE): survival results from an adaptive, multiarm, multistage, platform randomised controlled trial

BACKGROUND Long-term hormone therapy has been the standard of care for advanced prostate cancer since the 1940s. STAMPEDE is a randomised controlled trial using a multiarm, multistage platform design. It recruits men with high-risk, locally advanced, metastatic or recurrent prostate cancer who are starting first-line long-term hormone therapy. We report primary survival results for three research comparisons testing the addition of zoledronic acid, docetaxel, or their combination to standard of care versus standard of care alone. METHODS Standard of care was hormone therapy for at least 2 years; radiotherapy was encouraged for men with N0M0 disease to November, 2011, then mandated; radiotherapy was optional for men with node-positive non-metastatic (N+M0) disease. Stratified randomisation (via minimisation) allocated men 2:1:1:1 to standard of care only (SOC-only; control), standard of care plus zoledronic acid (SOC + ZA), standard of care plus docetaxel (SOC + Doc), or standard of care with both zoledronic acid and docetaxel (SOC + ZA + Doc). Zoledronic acid (4 mg) was given for six 3-weekly cycles, then 4-weekly until 2 years, and docetaxel (75 mg/m(2)) for six 3-weekly cycles with prednisolone 10 mg daily. There was no blinding to treatment allocation. The primary outcome measure was overall survival. Pairwise comparisons of research versus control had 90% power at 2·5% one-sided α for hazard ratio (HR) 0·75, requiring roughly 400 control arm deaths. Statistical analyses were undertaken with standard log-rank-type methods for time-to-event data, with hazard ratios (HRs) and 95% CIs derived from adjusted Cox models. This trial is registered at ClinicalTrials.gov (NCT00268476) and ControlledTrials.com (ISRCTN78818544). FINDINGS 2962 men were randomly assigned to four groups between Oct 5, 2005, and March 31, 2013. Median age was 65 years (IQR 60-71). 1817 (61%) men had M+ disease, 448 (15%) had N+/X M0, and 697 (24%) had N0M0. 165 (6%) men were previously treated with local therapy, and median prostate-specific antigen was 65 ng/mL (IQR 23-184). Median follow-up was 43 months (IQR 30-60). There were 415 deaths in the control group (347 [84%] prostate cancer). Median overall survival was 71 months (IQR 32 to not reached) for SOC-only, not reached (32 to not reached) for SOC + ZA (HR 0·94, 95% CI 0·79-1·11; p=0·450), 81 months (41 to not reached) for SOC + Doc (0·78, 0·66-0·93; p=0·006), and 76 months (39 to not reached) for SOC + ZA + Doc (0·82, 0·69-0·97; p=0·022). There was no evidence of heterogeneity in treatment effect (for any of the treatments) across prespecified subsets. Grade 3-5 adverse events were reported for 399 (32%) patients receiving SOC, 197 (32%) receiving SOC + ZA, 288 (52%) receiving SOC + Doc, and 269 (52%) receiving SOC + ZA + Doc. INTERPRETATION Zoledronic acid showed no evidence of survival improvement and should not be part of standard of care for this population. Docetaxel chemotherapy, given at the time of long-term hormone therapy initiation, showed evidence of improved survival accompanied by an increase in adverse events. Docetaxel treatment should become part of standard of care for adequately fit men commencing long-term hormone therapy. FUNDING Cancer Research UK, Medical Research Council, Novartis, Sanofi-Aventis, Pfizer, Janssen, Astellas, NIHR Clinical Research Network, Swiss Group for Clinical Cancer Research.

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^