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

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating

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

Physical and optical characteristics of heavily melted “rotten” Arctic sea ice

Field investigations of the properties of heavily melted “rotten” Arctic sea ice were carried out on shorefast and drifting ice off the coast of Utqiaġvik (formerly Barrow), Alaska, during the melt season. While no formal criteria exist to qualify when ice becomes rotten, the objective of this study was to sample melting ice at the point at which its structural and optical properties are sufficiently advanced beyond the peak of the summer season. Baseline data on the physical (temperature, salinity, density, microstructure) and optical (light scattering) properties of shorefast ice were recorded in May and June 2015. In July of both 2015 and 2017, small boats were used to access drifting rotten ice within ∼32&thinsp;km of Utqiaġvik. Measurements showed that pore space increased as ice temperature increased (−8 to 0&thinsp;∘C), ice salinity decreased (10 to 0&thinsp;ppt), and bulk density decreased (0.9 to 0.6&thinsp;g&thinsp;cm−3). Changes in pore space were characterized with thin-section microphotography and X-ray micro-computed tomography in the laboratory. These analyses yielded changes in average brine inclusion number density (which decreased from 32 to 0.01&thinsp;mm−3), mean pore size (which increased from 80&thinsp;µm to 3&thinsp;mm), and total porosity (increased from 0&thinsp;% to &gt;&thinsp;45&thinsp;%) and structural anisotropy (variable, with values of generally less than 0.7). Additionally, light-scattering coefficients of the ice increased from approximately 0.06 to &gt;&thinsp;0.35&thinsp;cm−1 as the ice melt progressed. Together, these findings indicate that the properties of Arctic sea ice at the end of melt season are significantly distinct from those of often-studied summertime ice. If such rotten ice were to become more prevalent in a warmer Arctic with longer melt seasons, this could have implications for the exchange of fluid and heat at the ocean surface.</p

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

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