Familial occurrence of chronic respiratory disease and familial resemblance in ventilatory capacity

One of the main hypotheses of the Tecumseh Study is that no matter whether genetic, constitutional or environmental factors are involved, new cases of disease will occur among family members of affected persons. During the second cycle of examinations, 82 per cent of the population were examined. Eighty-nine per cent of these 9226 persons had one or most first-degree relatives who was also a member of the study population. We have found that the prevalences of chronic bronchitis, asthma and allergic rhinitis were higher in the offspring when one or both parents were affected than when neither was. Clustering of these conditions also occurred in affected sibships but there was evidence of disease aggregation among spouses only for chronic bronchitis. There were statistically significant correlations of parents' lung function variables with those of their children and these were greater at younger than older ages and when parent and child were of the same sex. Intraclass correlation coefficients of F.E.V.1.0 scores for two-person sibships were statistically significant and varied with sex and age of the sibs. Statistically significant correlations were also found between F.E.V.1.0 scores of spouses but these were appreciably smaller than those between first-degree relatives. The scores of the variables are age- and height-adjusted and therefore, the resemblances in lung function are not merely a reflection of resemblances in height.The patterns of clustering and resemblance vary with disease as well as with age and sex. They implicate both environmental and genetic factors as determinants of chronic bronchitis, asthma, allergic rhinitis and level of ventilatory capacity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/22086/1/0000510.pd

Adult respiratory distress syndrome in neutropenic patients

The precise pathophysiologic mechanisms that cause the adult respiratory distress syndrome are unknown. Indirect evidence from human studies and extrapolations from animal models have suggested that phagocytic neutrophils are important in the pathogenesis of this disease. To further evaluate the role of neutrophils, the frequency of neutropenia in 18 bacteremic patients who had the adult respiratory distress syndrome was compared with that in a control group who had bacteremia alone. Three of 18 patients in the group with the adult respiratory distress syndrome were neutropenic as opposed to one of 18 in the control group (p >0.6). Histologic examination of the lungs from two patients with the adult respiratory distress syndrome and neutropenia demonstrated the absence of neutrophils. It is likely that there are many pathways that lead to the adult respiratory distress syndrome. Although neutrophils may be involved in some of these processes, this study demonstrates that neutrophils are not required for the development of the syndrome. In the appropriate clinical setting, the diagnosis of the adult respiratory distress syndrome should not be excluded solely because of neutropenia.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26450/1/0000538.pd

Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions

Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment – by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots

Biophysics and systems biology

Biophysics at the systems level, as distinct from molecular biophysics, acquired its most famous paradigm in the work of Hodgkin and Huxley, who integrated their equations for the nerve impulse in 1952. Their approach has since been extended to other organs of the body, notably including the heart. The modern field of computational biology has expanded rapidly during the first decade of the twenty-first century and, through its contribution to what is now called systems biology, it is set to revise many of the fundamental principles of biology, including the relations between genotypes and phenotypes. Evolutionary theory, in particular, will require re-assessment. To succeed in this, computational and systems biology will need to develop the theoretical framework required to deal with multilevel interactions. While computational power is necessary, and is forthcoming, it is not sufficient. We will also require mathematical insight, perhaps of a nature we have not yet identified. This article is therefore also a challenge to mathematicians to develop such insights

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller–Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated

Examining assumptions regarding valid electronic monitoring of medication therapy: development of a validation framework and its application on a European sample of kidney transplant patients

BACKGROUND: Electronic monitoring (EM) is used increasingly to measure medication non-adherence. Unbiased EM assessment requires fulfillment of assumptions. The purpose of this study was to determine assumptions needed for internal and external validity of EM measurement. To test internal validity, we examined if (1) EM equipment functioned correctly, (2) if all EM bottle openings corresponded to actual drug intake, and (3) if EM did not influence a patient's normal adherence behavior. To assess external validity, we examined if there were indications that using EM affected the sample representativeness. METHODS: We used data from the Supporting Medication Adherence in Renal Transplantation (SMART) study, which included 250 adult renal transplant patients whose adherence to immunosuppressive drugs was measured during 3 months with the Medication Event Monitoring System (MEMS). Internal validity was determined by assessing the prevalence of nonfunctioning EM systems, the prevalence of patient-reported discrepancies between cap openings and actual intakes (using contemporaneous notes and interview at the end of the study), and by exploring whether adherence was initially uncharacteristically high and decreased over time (an indication of a possible EM intervention effect). Sample representativeness was examined by screening for differences between participants and non-participants or drop outs on non-adherence. RESULTS: Our analysis revealed that some assumptions were not fulfilled: 1) one cap malfunctioned (0.4%), 2) self-reported mismatches between bottle openings and actual drug intake occurred in 62% of the patients (n = 155), and 3) adherence decreased over the first 5 weeks of the monitoring, indicating that EM had a waning intervention effect. CONCLUSION: The validity assumptions presented in this article should be checked in future studies using EM as a measure of medication non-adherence

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte