Intentional polarity conversion of AlN epitaxial layers by oxygen

Nitride materials (AlN, GaN, InN and their alloys) are commonly used in optoelectronics, high-power and high-frequency electronics. Polarity is the essential characteristic of these materials: when grown along c-direction, the films may exhibit either N- or metal-polar surface, which strongly influences their physical properties. The possibility to manipulate the polarity during growth allows to establish unique polarity in nitride thin films and nanowires for existing applications but also opens up new opportunities for device applications, e.g., in non-linear optics. In this work, we show that the polarity of an AlN film can intentionally be inverted by applying an oxygen plasma. We anneal an initially mixed-polar AlN film, grown on sapphire substrate by metal-organic vapor phase epitaxy (MOVPE), with an oxygen plasma in a molecular beam epitaxy (MBE) chamber; then, back in MOVPE, we deposit a 200 nm thick AlN film on top of the oxygen-treated surface. Analysis by high-resolution probe-corrected scanning transmission electron microscopy (STEM) imaging and electron energy-loss spectroscopy (EELS) evidences a switch of the N-polar domains to metal polarity. The polarity inversion is mediated through the formation of a thin AlxOyNz layer on the surface of the initial mixed polar film, induced by the oxygen annealing

Time to revisit the passive overconsumption hypothesis?:Humans show sensitivity to calories in energy-rich meals

BACKGROUND: A possible driver of obesity is insensitivity (passive overconsumption) to food energy density (ED, kcal/g); however, it is unclear whether this insensitivity applies to all meals. OBJECTIVES: We assessed the influence of ED on energy intake (kcal) across a broad and continuous range of EDs comprised of noncovertly manipulated, real-world meals. We also allowed for the possibility that the association between energy intake and ED is nonlinear. METHODS: We completed a secondary analysis of 1519 meals which occurred in a controlled environment as part of a study conducted by Hall and colleagues to assess the effects of food ultra-processing on energy intake. To establish the generalizability of the findings, the analyses were repeated in 32,162 meals collected from free-living humans using data from the UK National Diet and Nutrition Survey (NDNS). Segmented regressions were performed to establish ED “breakpoints” at which the association between consumed meal ED and mean centered meal caloric intake (kcal) changed. RESULTS: Significant breakpoints were found in both the Hall et al. data set (1.41 kcal/g) and the NDNS data set (1.75 and 2.94 kcal/g). Centered meal caloric intake did not increase linearly with consumed meal ED, and this pattern was captured by a 2-component (“volume” and “calorie content” [biologically derived from the sensing of fat, carbohydrate, and protein]) model of physical meal size (g), in which volume is the dominant signal with lower energy-dense foods and calorie content is the dominant signal with higher energy-dense foods. CONCLUSIONS: These analyses reveal that, on some level, humans are sensitive to the energy content of meals and adjust meal size to minimize the acute aversive effects of overconsumption. Future research should consider the relative importance of volume and calorie-content signals, and how individual differences impact everyday dietary behavior and energy balance

Looking back on 50 years of literature to understand the potential impact of influenza on extrapulmonary medical outcomes

We conducted a scoping review of the epidemiological literature from the past 50 years to document the contribution of influenza virus infection to extrapulmonary clinical outcomes. We identified 99 publications reporting 243 associations using many study designs, exposure and outcome definitions, and methods. Laboratory confirmation of influenza was used in only 28 (12%) estimates, mostly in case-control and self-controlled case series study designs. We identified 50 individual clinical conditions associated with influenza. The most numerous estimates were of cardiocirculatory diseases, neurological/neuromuscular diseases, and fetal/newborn disorders, with myocardial infarction the most common individual outcome. Due to heterogeneity, we could not generate summary estimates of effect size, but of 130 relative effect estimates, 105 (81%) indicated an elevated risk of extrapulmonary outcome with influenza exposure. The literature is indicative of systemic complications of influenza virus infection, the requirement for more effective influenza control, and a need for robust confirmatory studies

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

Performance status is the most powerful risk factor for early death among patients with advanced soft tissue sarcoma The European Organisation for Research and Treatment of Cancer – Soft Tissue and Bone Sarcoma Group (STBSG) and French Sarcoma Group (FSG) study

BACKGROUND: We investigated prognostic factors (PFs) for 90-day mortality in a large cohort of advanced/metastatic soft tissue sarcoma (STS) patients treated with first-line chemotherapy. METHODS: The PFs were identified by both logistic regression analysis and probability tree analysis in patients captured in the Soft Tissue and Bone Sarcoma Group (STBSG) database (3002 patients). Scores derived from the logistic regression analysis and algorithms derived from probability tree analysis were subsequently validated in an independent study cohort from the French Sarcoma Group (FSG) database (404 patients). RESULTS: The 90-day mortality rate was 8.6 and 4.5% in both cohorts. The logistic regression analysis retained performance status (PS; odds ratio (OR) = 3.83 if PS = 1, OR = 12.00 if PS >= 2), presence of liver metastasis (OR = 2.37) and rare site metastasis (OR = 2.00) as PFs for early death. The CHAID analysis retained PS as a major discriminator followed by histological grade (only for patients with PS >= 2). In both models, PS was the most powerful PF for 90-day mortality. CONCLUSION: Performance status has to be taken into account in the design of further clinical trials and is one of the most important parameters to guide patient management. For those patients with poor PS, expected benefits from therapy should be weighed up carefully against the anticipated toxicities. British Journal of Cancer (2011) 104, 1544-1550. doi: 10.1038/bjc.2011.136 www.bjcancer.com Published online 19 April 2011 (C) 2011 Cancer Research U

Valence-dependent influence of serotonin depletion on model-based choice strategy.

Human decision-making arises from both reflective and reflexive mechanisms, which underpin goal-directed and habitual behavioural control. Computationally, these two systems of behavioural control have been described by different learning algorithms, model-based and model-free learning, respectively. Here, we investigated the effect of diminished serotonin (5-hydroxytryptamine) neurotransmission using dietary tryptophan depletion (TD) in healthy volunteers on the performance of a two-stage decision-making task, which allows discrimination between model-free and model-based behavioural strategies. A novel version of the task was used, which not only examined choice balance for monetary reward but also for punishment (monetary loss). TD impaired goal-directed (model-based) behaviour in the reward condition, but promoted it under punishment. This effect on appetitive and aversive goal-directed behaviour is likely mediated by alteration of the average reward representation produced by TD, which is consistent with previous studies. Overall, the major implication of this study is that serotonin differentially affects goal-directed learning as a function of affective valence. These findings are relevant for a further understanding of psychiatric disorders associated with breakdown of goal-directed behavioural control such as obsessive-compulsive disorders or addictions.This research was funded by Wellcome Trust Grants awarded to VV (Intermediate WT Fellowship) and Programme Grant (089589/Z/09/Z) awarded to TWR, BJE, ACR, JWD and BJS. It was conducted at the Behavioural and Clinical Neuroscience Institute, which is supported by a joint award from the Medical Research Council and Wellcome Trust (G00001354). YW was supported by the Fyssen Foundation. SP is supported by Marie Curie Intra-European Fellowship (FP7-People-2012-IEF).This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/mp.2015.4

Constraining bridges between levels of analysis : a computational justification for locally Bayesian learning

Different levels of analysis provide different insights into behavior: computational-level analyses determine the problem an organism must solve and algorithmic-level analyses determine the mechanisms that drive behavior. However, many attempts to model behavior are pitched at a single level of analysis. Research into human and animal learning provides a prime example, with some researchers using computational-level models to understand the sensitivity organisms display to environmental statistics but other researchers using algorithmic-level models to understand organisms’ trial order effects, including effects of primacy and recency. Recently, attempts have been made to bridge these two levels of analysis. Locally Bayesian Learning (LBL) creates a bridge by taking a view inspired by evolutionary psychology: Our minds are composed of modules that are each individually Bayesian but communicate with restricted messages. A different inspiration comes from computer science and statistics: Our brains are implementing the algorithms developed for approximating complex probability distributions. We show that these different inspirations for how to bridge levels of analysis are not necessarily in conflict by developing a computational justification for LBL. We demonstrate that a scheme that maximizes computational fidelity while using a restricted factorized representation produces the trial order effects that motivated the development of LBL. This scheme uses the same modular motivation as LBL, passing messages about the attended cues between modules, but does not use the rapid shifts of attention considered key for the LBL approximation. This work illustrates a new way of tying together psychological and computational constraints

Simple methodology for the quantitative analysis of fatty acids in human red blood cells

In the last years, there has been an increasing interest in evaluating possible relations between fatty acid (FA) patterns and the risk for chronic diseases. Due to the long life span (120 days) of red blood cells (RBCs), their FA profile reflects a longer term dietary intake and was recently suggested to be used as an appropriate biomarker to investigate correlations between FA metabolism and diseases. Therefore, the aim of this work was to develop and validate a simple and fast methodology for the quantification of a broad range of FAs in RBCs using gas chromatography with flame ionization detector, as a more common and affordable equipment suitable for biomedical and nutritional studies including a large number of samples. For this purpose, different sample preparation protocols were tested and compared, including a classic two-step method (Folch method) with modifications and different one-step methods, in which lipid extraction and derivatization were performed simultaneously. For the one-step methods, different methylation periods and the inclusion of a saponification reaction were evaluated. Differences in absolute FA concentrations were observed among the tested methods, in particular for some metabolically relevant FAs such as trans elaidic acid and eicosapentaenoic acid. The one-step method with saponification and 60 min of methylation time was selected since it allowed the identification of a higher number of FAs, and was further submitted to in-house validation. The proposed methodology provides a simple, fast and accurate tool to quantitatively analyse FAs in human RBCs, useful for clinical and nutritional studies.This work received financial support from the European Union (FEDER funds through COMPETE) and National Funds (FCT, Fundação para a Ciência e Tecnologia) through project PTDC/SAU-ENB/116929/2010 and EXPL/EMS-SIS/2215/2013. ROR acknowledges PhD scholarship SFRH/BD/97658/2013 attributed by FCT (Fundação para a Ciência e Tecnologia).info:eu-repo/semantics/publishedVersio