Challenges and Opportunities: What Can We Learn from Patients Living with Chronic Musculoskeletal Conditions, Health Professionals and Carers about the Concept of Health Literacy Using Qualitative Methods of Inquiry?

The field of health literacy continues to evolve and concern public health researchers and yet remains a largely overlooked concept elsewhere in the healthcare system. We conducted focus group discussions in England UK, about the concept of health literacy with older patients with chronic musculoskeletal conditions (mean age = 73.4 years), carers and health professionals. Our research posed methodological, intellectual and practical challenges. Gaps in conceptualisation and expectations were revealed, reiterating deficiencies in predominant models for understanding health literacy and methodological shortcomings of using focus groups in qualitative research for this topic. Building on this unique insight into what the concept of health literacy meant to participants, we present analysis of our findings on factors perceived to foster and inhibit health literacy and on the issue of responsibility in health literacy. Patients saw health literacy as a result of an inconsistent interactive process and the implications as wide ranging; healthcare professionals had more heterogeneous views. All focus group discussants agreed that health literacy most benefited from good inter-personal communication and partnership. By proposing a needs-based approach to health literacy we offer an alternative way of conceptualising health literacy to help improve the health of older people with chronic conditions

The Systems Biology Research Tool: evolvable open-source software

BACKGROUND: Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput) experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. RESULTS: We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT) to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. CONCLUSION: The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability), to facilitate cooperation among researchers, and to expedite progress in the field of systems biology

Exhaustive identification of steady state cycles in large stoichiometric networks

BACKGROUND: Identifying cyclic pathways in chemical reaction networks is important, because such cycles may indicate in silico violation of energy conservation, or the existence of feedback in vivo. Unfortunately, our ability to identify cycles in stoichiometric networks, such as signal transduction and genome-scale metabolic networks, has been hampered by the computational complexity of the methods currently used. RESULTS: We describe a new algorithm for the identification of cycles in stoichiometric networks, and we compare its performance to two others by exhaustively identifying the cycles contained in the genome-scale metabolic networks of H. pylori, M. barkeri, E. coli, and S. cerevisiae. Our algorithm can substantially decrease both the execution time and maximum memory usage in comparison to the two previous algorithms. CONCLUSION: The algorithm we describe improves our ability to study large, real-world, biochemical reaction networks, although additional methodological improvements are desirable

Mycobacterium tuberculosis Responds to Chloride and pH as Synergistic Cues to the Immune Status of its Host Cell

PubMed ID: 23592993This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Stroke risk perception among participants of a stroke awareness campaign

BACKGROUND: Subjective risk factor perception is an important component of the motivation to change unhealthy life styles. While prior studies assessed cardiovascular risk factor knowledge, little is known about determinants of the individual perception of stroke risk. METHODS: Survey by mailed questionnaire among 1483 participants of a prior public stroke campaign in Germany. Participants had been informed about their individual stroke risk based on the Framingham stroke risk score. Stroke risk factor knowledge, perception of lifetime stroke risk and risk factor status were included in the questionnaire, and the determinants of good risk factor knowledge and high stroke risk perception were identified using logistic regression models. RESULTS: Overall stroke risk factor knowledge was good with 67–96% of the participants recognizing established risk factors. The two exceptions were diabetes (recognized by 49%) and myocardial infarction (57%). Knowledge of a specific factor was superior among those affected by it. 13% of all participants considered themselves of having a high stroke risk, 55% indicated a moderate risk. All major risk factors contributed significantly to the perception of being at high stroke risk, but the effects of age, sex and education were non-significant. Poor self-rated health was additionally associated with high individual stroke risk perception. CONCLUSION: Stroke risk factor knowledge was high in this study. The self perception of an increased stroke risk was associated with established risk factors as well as low perception of general health

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

The association of health literacy with adherence in older 2 adults, and its role in interventions: a systematic meta-review

Background: Low health literacy is a common problem among older adults. It is often suggested to be associated with poor adherence. This suggested association implies a need for effective adherence interventions in low health literate people. However, previous reviews show mixed results on the association between low health literacy and poor adherence. A systematic meta-review of systematic reviews was conducted to study the association between health literacy and adherence in adults above the age of 50. Evidence for the effectiveness of adherence interventions among adults in this older age group with low health literacy was also explored. Methods: Eight electronic databases (MEDLINE, ERIC, EMBASE, PsycINFO, CINAHL, DARE, the Cochrane Library, and Web of Knowledge) were searched using a variety of keywords regarding health literacy and adherence. Additionally, references of identified articles were checked. Systematic reviews were included if they assessed the association between health literacy and adherence or evaluated the effectiveness of interventions to improve adherence in adults with low health literacy. The AMSTAR tool was used to assess the quality of the included reviews. The selection procedure, data-extraction, and quality assessment were performed by two independent reviewers. Seventeen reviews were selected for inclusion. Results: Reviews varied widely in quality. Both reviews of high and low quality found only weak or mixed associations between health literacy and adherence among older adults. Reviews report on seven studies that assess the effectiveness of adherence interventions among low health literate older adults. The results suggest that some adherence interventions are effective for this group. The interventions described in the reviews focused mainly on education and on lowering the health literacy demands of adherence instructions. No conclusions could be drawn about which type of intervention could be most beneficial for this population. Conclusions: Evidence on the association between health literacy and adherence in older adults is relatively weak. Adherence interventions are potentially effective for the vulnerable population of older adults with low levels of health literacy, but the evidence on this topic is limited. Further research is needed on the association between health literacy and general health behavior, and on the effectiveness of interventions

Surface electrons at plasma walls

In this chapter we introduce a microscopic modelling of the surplus electrons on the plasma wall which complements the classical description of the plasma sheath. First we introduce a model for the electron surface layer to study the quasistationary electron distribution and the potential at an unbiased plasma wall. Then we calculate sticking coefficients and desorption times for electron trapping in the image states. Finally we study how surplus electrons affect light scattering and how charge signatures offer the possibility of a novel charge measurement for dust grains.Comment: To appear in Complex Plasmas: Scientific Challenges and Technological Opportunities, Editors: M. Bonitz, K. Becker, J. Lopez and H. Thomse

Magnetic resonance lung function – a breakthrough for lung imaging and functional assessment? A phantom study and clinical trial

BACKGROUND: Chronic lung diseases are a major issue in public health. A serial pulmonary assessment using imaging techniques free of ionizing radiation and which provides early information on local function impairment would therefore be a considerably important development. Magnetic resonance imaging (MRI) is a powerful tool for the static and dynamic imaging of many organs. Its application in lung imaging however, has been limited due to the low water content of the lung and the artefacts evident at air-tissue interfaces. Many attempts have been made to visualize local ventilation using the inhalation of hyperpolarized gases or gadolinium aerosol responding to MRI. None of these methods are applicable for broad clinical use as they require specific equipment. METHODS: We have shown previously that low-field MRI can be used for static imaging of the lung. Here we show that mathematical processing of data derived from serial MRI scans during the respiratory cycle produces good quality images of local ventilation without any contrast agent. A phantom study and investigations in 85 patients were performed. RESULTS: The phantom study proved our theoretical considerations. In 99 patient investigations good correlation (r = 0.8; p ≤ 0.001) was seen for pulmonary function tests and MR ventilation measurements. Small ventilation defects were visualized. CONCLUSION: With this method, ventilation defects can be diagnosed long before any imaging or pulmonary function test will indicate disease. This surprisingly simple approach could easily be incorporated in clinical routine and may be a breakthrough for lung imaging and functional assessment

Deciphering the Chemical Basis of Nestmate Recognition

Social insects maintain colony cohesion by recognizing and, if necessary, discriminating against conspecifics that are not part of the colony. This recognition ability is encoded by a complex mixture of cuticular hydrocarbons (CHCs), although it is largely unclear how social insects interpret such a multifaceted signal. CHC profiles often contain several series of homologous hydrocarbons, possessing the same methyl branch position but differing in chain length (e.g., 15-methyl-pentatriacontane, 15-methyl-heptatriacontane, 15-methyl-nonatriacontane). Recent studies have revealed that within species these homologs can occur in correlated concentrations. In such cases, single compounds may convey the same information as the homologs. In this study, we used behavioral bioassays to explore how social insects perceive and interpret different hydrocarbons. We tested the aggressive response of Argentine ants, Linepithema humile, toward nest-mate CHC profiles that were augmented with one of eight synthetic hydrocarbons that differed in branch position, chain length, or both. We found that Argentine ants showed similar levels of aggression toward nest-mate CHC profiles augmented with compounds that had the same branch position but differed in chain length. Conversely, Argentine ants displayed different levels of aggression toward nest-mate CHC profiles augmented with compounds that had different branch positions but the same chain length. While this was true in almost all cases, one CHC we tested elicited a greater aggressive response than its homologs. Interestingly, this was the only compound that did not occur naturally in correlated concentrations with its homologs in CHC profiles. Combined, these data suggest that CHCs of a homologous series elicit the same aggressive response because they convey the same information, rather than Argentine ants being unable to discriminate between different homologs. This study contributes to our understanding of the chemical basis of nestmate recognition by showing that, similar to spoken language, the chemical language of social insects contains “synonyms,” chemicals that differ in structure, but not meaning