Chemotactic response and adaptation dynamics in Escherichia coli

Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.Comment: accepted for publication in PLoS Computational Biology; manuscript (19 pages, 5 figures) and supplementary information; added additional clarification on alternative adaptation models in supplementary informatio

Two-neutron knockout from neutron-deficient 34^{34}Ar, 30^{30}S, and 26^{26}Si

Two-neutron knockout reactions from nuclei in the proximity of the proton dripline have been studied using intermediate-energy beams of neutron-deficient $^{34}$Ar, $^{30}$S, and $^{26}$Si. The inclusive cross sections, and also the partial cross sections for the population of individual bound final states of the $^{32}$Ar, $^{28}$S and $^{24}$Si knockout residues, have been determined using the combination of particle and $\gamma$-ray spectroscopy. Similar to the two-proton knockout mechanism on the neutron-rich side of the nuclear chart, these two-neutron removal reactions from already neutron-deficient nuclei are also shown to be consistent with a direct reaction mechanism.Comment: Phys. Rev. C, rapid communication, in pres

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

Effect of zinc intake on serum/plasma zinc status in infants: A meta-analysis

A systematic review and meta-analysis of available RCTs was conducted to evaluate the effect of zinc (Zn) intake on serum/plasma Zn status in infants. Out of 5500 studies identified through electronic searches and reference lists, 9 RCTs were selected after applying the exclusion/inclusion criteria. The influence of zinc intake on serum/plasma Zn concentration was considered in the overall meta-analysis. Other variables were also taken into account as possible effect modifiers: doses of zinc intake, intervention duration, nutritional status and risk of bias. From each selected study, final measures of serum/plasma Zn were assessed. RESULTS: The pooled β of status was 0.09 (95%CI 0.06 to 0.12). However, a substantial heterogeneity was present in the analyses (I2=95%; p=0.00001). When we performed a meta-regression, the effect of Zn intake on serum/plasma Zn status changed depending on the duration of the intervention, the dose of supplementation and the nutritional situation (p ANCOVA= 0.005; 20 weeks). A positive effect was seen also when doses ranged from 8.1 to 12 mg/day. In all cases, the pooled β showed high evidence of heterogeneity. CONCLUSION: Zinc supplementation increases serum/plasma Zn status in infants, although high evidence of heterogeneity was found. Further standardized research is urgently needed to reach evidence-based conclusions to clarify the role of zinc supplementation upon infant serum/plasma Zn status, particularly in Europe

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions

Background Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Results Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. Conclusions The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions

Measurement of GEp/GMp in ep -> ep to Q2 = 5.6 GeV2

The ratio of the electric and magnetic form factors of the proton, GEp/GMp, was measured at the Thomas Jefferson National Accelerator Facility (JLab) using the recoil polarization technique. The ratio of the form factors is directly proportional to the ratio of the transverse to longitudinal components of the polarization of the recoil proton in the elastic $\vec ep \to e\vec p$ reaction. The new data presented in this article span the range 3.5 < Q2 < 5.6 GeV2 and are well described by a linear Q2 fit. Also, the ratio QF2p/F1p reaches a constant value above Q2=2 GeV2.Comment: 6 pages, 4 figures Added two names to the main author lis

Modeling a bacterial ecosystem through chemotaxis simulation of a single cell

International audienceWe present in this paper an artificial life ecosystem in which bacteria are evolved to perform chemotaxis. In this system, surviving bacteria have to overcome the problems of detecting resources (or sensing the environment), modulating their motion to generate a foraging behavior, and communicating with their kin to produce more sophisticated behaviors. A cell’s chemotactic pathway is modulated by a hybrid approach that uses an algebraic model for the receptor clusters activity, an ordinary differential equation for the adaptation dynamics, and a metabolic model that converts nutrients into biomass. The results show some analysis of the motion obtained from some bacteria and their effects on the evolved population behavior. The evolutionary process improves the bacteria’s ability to react to their environment, enhancing their growth and allowing them to better survive. As future work, we propose to investigate the effect of emergent bacterial communication as new species arise, and to explore the dynamics of colonies

Core components for effective infection prevention and control programmes: new WHO evidence-based recommendations

Abstract Health care-associated infections (HAI) are a major public health problem with a significant impact on morbidity, mortality and quality of life. They represent also an important economic burden to health systems worldwide. However, a large proportion of HAI are preventable through effective infection prevention and control (IPC) measures. Improvements in IPC at the national and facility level are critical for the successful containment of antimicrobial resistance and the prevention of HAI, including outbreaks of highly transmissible diseases through high quality care within the context of universal health coverage. Given the limited availability of IPC evidence-based guidance and standards, the World Health Organization (WHO) decided to prioritize the development of global recommendations on the core components of effective IPC programmes both at the national and acute health care facility level, based on systematic literature reviews and expert consensus. The aim of the guideline development process was to identify the evidence and evaluate its quality, consider patient values and preferences, resource implications, and the feasibility and acceptability of the recommendations. As a result, 11 recommendations and three good practice statements are presented here, including a summary of the supporting evidence, and form the substance of a new WHO IPC guideline

PainDroid: An android-based virtual reality application for pain assessment

Earlier studies in the field of pain research suggest that little efficient intervention currently exists in response to the exponential increase in the prevalence of pain. In this paper, we present an Android application (PainDroid) with multimodal functionality that could be enhanced with Virtual Reality (VR) technology, which has been designed for the purpose of improving the assessment of this notoriously difficult medical concern. Pain- Droid has been evaluated for its usability and acceptability with a pilot group of potential users and clinicians, with initial results suggesting that it can be an effective and usable tool for improving the assessment of pain. Participant experiences indicated that the application was easy to use and the potential of the application was similarly appreciated by the clinicians involved in the evaluation. Our findings may be of considerable interest to healthcare providers, policy makers, and other parties that might be actively involved in the area of pain and VR research

Can sacrificial feeding areas protect aquatic plants from herbivore grazing? Using behavioural ecology to inform wildlife management

Effective wildlife management is needed for conservation, economic and human well-being objectives. However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement. New methods which address these issues and offer effective wildlife management are required. We used an individual-based model to predict the efficacy of a sacrificial feeding area in preventing grazing damage by mute swans (Cygnus olor) to adjacent river vegetation of high conservation and economic value. The accuracy of model predictions was assessed by a comparison with observed field data, whilst prediction robustness was evaluated using a sensitivity analysis. We used repeated simulations to evaluate how the efficacy of the sacrificial feeding area was regulated by (i) food quantity, (ii) food quality, and (iii) the functional response of the forager. Our model gave accurate predictions of aquatic plant biomass, carrying capacity, swan mortality, swan foraging effort, and river use. Our model predicted that increased sacrificial feeding area food quantity and quality would prevent the depletion of aquatic plant biomass by swans. When the functional response for vegetation in the sacrificial feeding area was increased, the food quantity and quality in the sacrificial feeding area required to protect adjacent aquatic plants were reduced. Our study demonstrates how the insights of behavioural ecology can be used to inform wildlife management. The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems