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

Modelling the cost-effectiveness of public awareness campaigns for the early detection of non-small-cell lung cancer

Background: Survival rates in lung cancer in England are significantly lower than in many similar countries. A range of Be Clear on Cancer (BCOC) campaigns have been conducted targeting lung cancer and found to improve the proportion of diagnoses at the early stage of disease. This paper considers the cost-effectiveness of such campaigns, evaluating the effect of both the regional and national BCOC campaigns on the stage distribution of non-small-cell lung cancer (NSCLC) at diagnosis. Methods: A natural history model of NSCLC was developed using incidence data, data elicited from clinical experts and model calibration techniques. This structure is used to consider the lifetime cost and quality-adjusted survival implications of the early awareness campaigns. Incremental cost-effectiveness ratios (ICERs) in terms of additional costs per quality-adjusted life-years (QALYs) gained are presented. Two scenario analyses were conducted to investigate the role of changes in the ‘worried-well’ population and the route of diagnosis that might occur as a result of the campaigns. Results: The base-case theoretical model found the regional and national early awareness campaigns to be associated with QALY gains of 289 and 178 QALYs and ICERs of d13 660 and d18 173 per QALY gained, respectively. The scenarios found that increases in the ‘worried-well’ population may impact the cost-effectiveness conclusions. Conclusions: Subject to the available evidence, the analysis suggests that early awareness campaigns in lung cancer have the potential to be cost-effective. However, significant additional research is required to address many of the limitations of this study. In addition, the estimated natural history model presents previously unavailable estimates of the prevalence and rate of disease progression in the undiagnosed population

Predicting Novel Binding Modes of Agonists to β Adrenergic Receptors Using All-Atom Molecular Dynamics Simulations

Understanding the binding mode of agonists to adrenergic receptors is crucial to enabling improved rational design of new therapeutic agents. However, so far the high conformational flexibility of G protein-coupled receptors has been an obstacle to obtaining structural information on agonist binding at atomic resolution. In this study, we report microsecond classical molecular dynamics simulations of β1 and β2 adrenergic receptors bound to the full agonist isoprenaline and in their unliganded form. These simulations show a novel agonist binding mode that differs from the one found for antagonists in the crystal structures and from the docking poses reported by in silico docking studies performed on rigid receptors. Internal water molecules contribute to the stabilization of novel interactions between ligand and receptor, both at the interface of helices V and VI with the catechol group of isoprenaline as well as at the interface of helices III and VII with the ethanolamine moiety of the ligand. Despite the fact that the characteristic N-C-C-OH motif is identical in the co-crystallized ligands and in the full agonist isoprenaline, the interaction network between this group and the anchor site formed by Asp(3.32) and Asn(7.39) is substantially different between agonists and inverse agonists/antagonists due to two water molecules that enter the cavity and contribute to the stabilization of a novel network of interactions. These new binding poses, together with observed conformational changes in the extracellular loops, suggest possible determinants of receptor specificity

Protein-enriched meal replacements do not adversely affect liver, kidney or bone density: an outpatient randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>There is concern that recommending protein-enriched meal replacements as part of a weight management program could lead to changes in biomarkers of liver or renal function and reductions in bone density. This study was designed as a placebo-controlled clinical trial utilizing two isocaloric meal plans utilizing either a high protein-enriched (HP) or a standard protein (SP) meal replacement in an outpatient weight loss program.</p> <p>Subjects/methods</p> <p>100 obese men and women over 30 years of age with a body mass index (BMI) between 27 to 40 kg/m²were randomized to one of two isocaloric weight loss meal plans 1). HP group: providing 2.2 g protein/kg of lean body mass (LBM)/day or 2). SP group: providing 1.1 g protein/kg LBM/day. Meal replacement (MR) was used twice daily (one meal, one snack) for 3 months and then once a day for 9 months. Body weight, lipid profiles, liver function, renal function and bone density were measured at baseline and 12 months.</p> <p>Results</p> <p>Seventy subjects completed the study. Both groups lost weight (HP -4.29 ± 5.90 kg vs. SP -4.66 ± 6.91 kg, p < 0.01) and there was no difference in weight loss observed between the groups at one year. There was no significant change noted in liver function [AST (HP -2.07 ± 10.32 U/L, p = 0.28; SP 0.27 ± 6.67 U/L, p = 0.820), ALT (HP -1.03 ± 10.08 U/L, p = 0.34; SP -2.6 ± 12.51 U/L, p = 0.24), bilirubin (HP 0.007 ± 0.33, U/L, p = 0.91; SP 0.07 ± 0.24 U/L, p = 0.120), alkaline phosphatase (HP 2.00 ± 9.07 U/L, p = 0.240; SP -2.12 ± 11.01 U/L, p = 0.280)], renal function [serum creatinine (HP 0.31 ± 1.89 mg/dL, p = 0.380; SP -0.05 ± 0.15 mg/dL, p = 0.060), urea nitrogen (HP 1.33 ± 4.68 mg/dL, p = 0.130; SP -0.24 ± 3.03 mg/dL, p = 0.650), 24 hour urine creatinine clearance (HP -0.02 ± 0.16 mL/min, p = 0.480; SP 1.18 ± 7.53 mL/min, p = 0.400), and calcium excretion (HP -0.41 ± 9.48 mg/24 hours, p = 0.830; SP -0.007 ± 6.76 mg/24 hours, p = 0.990)] or in bone mineral density by DEXA (HP 0.04 ± 0.19 g/cm², p = 0.210; SP -0.03 ± 0.17 g/cm², p = 0.320) in either group over one year.</p> <p>Conclusions</p> <p>These studies demonstrate that protein-enriched meals replacements as compared to standard meal replacements recommended for weight management do not have adverse effects on routine measures of liver function, renal function or bone density at one year. Clinicaltrial.gov: NCT01030354.</p

Quantitative Photo Activated Localization Microscopy: Unraveling the Effects of Photoblinking

In this work we discuss how to use photophysical information for improved quantitative measurements using Photo Activated Localization Microscopy (PALM) imaging. We introduce a method that reliably estimates the number of photoblinking molecules present in a biological sample and gives a robust way to quantify proteins at the single-cell level from PALM images. We apply this method to determine the amount of β2 adrenergic receptor, a prototypical G Protein Coupled Receptor, expressed on the plasma membrane of HeLa cells

Early Hypothalamic FTO Overexpression in Response to Maternal Obesity – Potential Contribution to Postweaning Hyperphagia

Intrauterine and postnatal overnutrition program hyperphagia, adiposity and glucose intolerance in offspring. Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene have been linked to increased risk of obesity. FTO is highly expressed in hypothalamic regions critical for energy balance and hyperphagic phenotypes were linked with FTO SNPs. As nutrition during fetal development can influence the expression of genes involved in metabolic function, we investigated the impact of maternal obesity on FTO.Female Sprague Dawley rats were exposed to chow or high fat diet (HFD) for 5 weeks before mating, throughout gestation and lactation. On postnatal day 1 (PND1), some litters were adjusted to 3 pups (vs. 12 control) to induce postnatal overnutrition. At PND20, rats were weaned onto chow or HFD for 15 weeks. FTO mRNA expression in the hypothalamus and liver, as well as hepatic markers of lipid metabolism were measured.At weaning, hypothalamic FTO mRNA expression was increased significantly in offspring of obese mothers and FTO was correlated with both visceral and epididymal fat mass (P<0.05); body weight approached significance (P = 0.07). Hepatic FTO and Fatty Acid Synthase mRNA expression were decreased by maternal obesity. At 18 weeks, FTO mRNA expression did not differ between groups; however body weight was significantly correlated with hypothalamic FTO. Postnatal HFD feeding significantly reduced hepatic Carnitine Palmitoyltransferase-1a but did not affect the expression of other hepatic markers investigated. FTO was not affected by chronic HFD feeding.Maternal obesity significantly impacted FTO expression in both hypothalamus and liver at weaning. Early overexpression of hypothalamic FTO correlated with increased adiposity and later food intake of siblings exposed to HFD suggesting upregulation of FTO may contribute to subsequent hyperphagia, in line with some human data. No effect of maternal obesity was observed on FTO in adulthood

Inverted Expression Profiles of Sex-Biased Genes in Response to Toxicant Perturbations and Diseases

10.1371/journal.pone.0056668PLoS ONE82

Modelling the transmission of healthcare associated infections: a systematic review.

BACKGROUND: Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. METHODS: MEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings. RESULTS: In total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries.The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data. CONCLUSIONS: Transmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models